Instructions to use ubergarm/GLM-4.7-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ubergarm/GLM-4.7-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf ubergarm/GLM-4.7-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf ubergarm/GLM-4.7-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ubergarm/GLM-4.7-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf ubergarm/GLM-4.7-GGUF:Q2_K
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf ubergarm/GLM-4.7-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf ubergarm/GLM-4.7-GGUF:Q2_K
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf ubergarm/GLM-4.7-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf ubergarm/GLM-4.7-GGUF:Q2_K
Use Docker
docker model run hf.co/ubergarm/GLM-4.7-GGUF:Q2_K
- LM Studio
- Jan
- vLLM
How to use ubergarm/GLM-4.7-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ubergarm/GLM-4.7-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ubergarm/GLM-4.7-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ubergarm/GLM-4.7-GGUF:Q2_K
- Ollama
How to use ubergarm/GLM-4.7-GGUF with Ollama:
ollama run hf.co/ubergarm/GLM-4.7-GGUF:Q2_K
- Unsloth Studio
How to use ubergarm/GLM-4.7-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ubergarm/GLM-4.7-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ubergarm/GLM-4.7-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ubergarm/GLM-4.7-GGUF to start chatting
- Pi
How to use ubergarm/GLM-4.7-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ubergarm/GLM-4.7-GGUF:Q2_K
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "ubergarm/GLM-4.7-GGUF:Q2_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use ubergarm/GLM-4.7-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ubergarm/GLM-4.7-GGUF:Q2_K
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "ubergarm/GLM-4.7-GGUF:Q2_K" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use ubergarm/GLM-4.7-GGUF with Docker Model Runner:
docker model run hf.co/ubergarm/GLM-4.7-GGUF:Q2_K
- Lemonade
How to use ubergarm/GLM-4.7-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ubergarm/GLM-4.7-GGUF:Q2_K
Run and chat with the model
lemonade run user.GLM-4.7-GGUF-Q2_K
List all available models
lemonade list
- Hermes Agent
How to use ubergarm/GLM-4.7-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ubergarm/GLM-4.7-GGUF:Q2_K
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default ubergarm/GLM-4.7-GGUF:Q2_K
Run Hermes
hermes
- Atomic Chat
| model=/mnt/data/models/ubergarm/GLM-4.7-GGUF/GLM-160x21B-4.7-BF16-00001-of-00015.gguf | |
| numactl -N ${SOCKET} -m ${SOCKET} \ | |
| ./build/bin/llama-imatrix \ | |
| --model "$model"\ | |
| -f ubergarm-imatrix-calibration-corpus-v02.txt \ | |
| -o /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat \ | |
| --no-fused-moe \ | |
| --no-fused-up-gate \ | |
| --no-fused-mul-multiadd \ | |
| --ctx-size 512 \ | |
| -ub 4096 -b 4096 \ | |
| --threads 96 \ | |
| --threads-batch 128 \ | |
| --no-mmap \ | |
| --numa numactl \ | |
| --verbosity 1 \ | |
| --layer-similarity | |
| CPU: using device CPU - 0 MiB free | |
| llama_model_loader: additional 14 GGUFs metadata loaded. | |
| llama_model_loader: loaded meta data with 49 key-value pairs and 1761 tensors from /mnt/data/models/ubergarm/GLM-4.7-GGUF/GLM-160x21B-4.7-BF16-00001-of-00015.gguf (version GGUF V3 (latest)) | |
| llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. | |
| llama_model_loader: - kv 0: general.architecture str = glm4moe | |
| llama_model_loader: - kv 1: general.type str = model | |
| llama_model_loader: - kv 2: general.sampling.temp f32 = 1.000000 | |
| llama_model_loader: - kv 3: general.name str = GLM 4.7 | |
| llama_model_loader: - kv 4: general.version str = 4.7 | |
| llama_model_loader: - kv 5: general.basename str = GLM | |
| llama_model_loader: - kv 6: general.size_label str = 160x21B | |
| llama_model_loader: - kv 7: general.license str = mit | |
| llama_model_loader: - kv 8: general.tags arr[str,1] = ["text-generation"] | |
| llama_model_loader: - kv 9: general.languages arr[str,2] = ["en", "zh"] | |
| llama_model_loader: - kv 10: glm4moe.block_count u32 = 93 | |
| llama_model_loader: - kv 11: glm4moe.context_length u32 = 202752 | |
| llama_model_loader: - kv 12: glm4moe.embedding_length u32 = 5120 | |
| llama_model_loader: - kv 13: glm4moe.feed_forward_length u32 = 12288 | |
| llama_model_loader: - kv 14: glm4moe.attention.head_count u32 = 96 | |
| llama_model_loader: - kv 15: glm4moe.attention.head_count_kv u32 = 8 | |
| llama_model_loader: - kv 16: glm4moe.rope.freq_base f32 = 1000000.000000 | |
| llama_model_loader: - kv 17: glm4moe.attention.layer_norm_rms_epsilon f32 = 0.000010 | |
| llama_model_loader: - kv 18: glm4moe.expert_used_count u32 = 8 | |
| llama_model_loader: - kv 19: glm4moe.expert_group_count u32 = 1 | |
| llama_model_loader: - kv 20: glm4moe.expert_group_used_count u32 = 1 | |
| llama_model_loader: - kv 21: glm4moe.attention.key_length u32 = 128 | |
| llama_model_loader: - kv 22: glm4moe.attention.value_length u32 = 128 | |
| llama_model_loader: - kv 23: general.file_type u32 = 32 | |
| llama_model_loader: - kv 24: glm4moe.rope.dimension_count u32 = 64 | |
| llama_model_loader: - kv 25: glm4moe.expert_count u32 = 160 | |
| llama_model_loader: - kv 26: glm4moe.expert_feed_forward_length u32 = 1536 | |
| llama_model_loader: - kv 27: glm4moe.expert_shared_count u32 = 1 | |
| llama_model_loader: - kv 28: glm4moe.leading_dense_block_count u32 = 3 | |
| llama_model_loader: - kv 29: glm4moe.expert_gating_func u32 = 2 | |
| llama_model_loader: - kv 30: glm4moe.expert_weights_scale f32 = 2.500000 | |
| llama_model_loader: - kv 31: glm4moe.expert_weights_norm bool = true | |
| llama_model_loader: - kv 32: glm4moe.nextn_predict_layers u32 = 1 | |
| llama_model_loader: - kv 33: general.quantization_version u32 = 2 | |
| llama_model_loader: - kv 34: tokenizer.ggml.model str = gpt2 | |
| llama_model_loader: - kv 35: tokenizer.ggml.pre str = glm4 | |
| llama_model_loader: - kv 36: tokenizer.ggml.tokens arr[str,151552] = ["!", "\"", "#", "$", "%", "&", "'", ...llama_model_loader: - kv 37: tokenizer.ggml.token_type arr[i32,151552] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...llama_model_loader: - kv 38: tokenizer.ggml.merges arr[str,318088] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... | |
| llama_model_loader: - kv 39: tokenizer.ggml.eos_token_id u32 = 151329 | |
| llama_model_loader: - kv 40: tokenizer.ggml.padding_token_id u32 = 151329 | |
| llama_model_loader: - kv 41: tokenizer.ggml.bos_token_id u32 = 151331 | |
| llama_model_loader: - kv 42: tokenizer.ggml.eot_token_id u32 = 151336 | |
| llama_model_loader: - kv 43: tokenizer.ggml.unknown_token_id u32 = 151329 | |
| llama_model_loader: - kv 44: tokenizer.ggml.eom_token_id u32 = 151338 | |
| llama_model_loader: - kv 45: tokenizer.chat_template str = [gMASK]<sop>\n{%- if tools -%}\n<|syste... | |
| llama_model_loader: - kv 46: split.no u16 = 0 | |
| llama_model_loader: - kv 47: split.count u16 = 15 | |
| llama_model_loader: - kv 48: split.tensors.count i32 = 1761 | |
| llama_model_loader: - type f32: 835 tensors | |
| llama_model_loader: - type bf16: 926 tensors | |
| load: special_eot_id is not in special_eog_ids - the tokenizer config may be incorrect | |
| load: special_eom_id is not in special_eog_ids - the tokenizer config may be incorrect | |
| load: printing all EOG tokens: | |
| load: - 151329 ('<|endoftext|>') | |
| load: - 151336 ('<|user|>') | |
| load: - 151338 ('<|observation|>') | |
| load: special tokens cache size = 36 | |
| load: token to piece cache size = 0.9713 MB | |
| llm_load_print_meta: format = GGUF V3 (latest) | |
| llm_load_print_meta: arch = glm4moe | |
| llm_load_print_meta: n_ctx_train = 202752 | |
| llm_load_print_meta: n_embd = 5120 | |
| llm_load_print_meta: n_layer = 93 | |
| llm_load_print_meta: n_head = 96 | |
| llm_load_print_meta: n_head_kv = 8 | |
| llm_load_print_meta: n_rot = 64 | |
| llm_load_print_meta: n_swa = 0 | |
| llm_load_print_meta: n_swa_pattern = 1 | |
| llm_load_print_meta: n_embd_head_k = 128 | |
| llm_load_print_meta: n_embd_head_v = 128 | |
| llm_load_print_meta: n_gqa = 12 | |
| llm_load_print_meta: n_embd_k_gqa = 1024 | |
| llm_load_print_meta: n_embd_v_gqa = 1024 | |
| llm_load_print_meta: f_norm_eps = 0.0e+00 | |
| llm_load_print_meta: f_norm_rms_eps = 1.0e-05 | |
| llm_load_print_meta: f_clamp_kqv = 0.0e+00 | |
| llm_load_print_meta: f_max_alibi_bias = 0.0e+00 | |
| llm_load_print_meta: f_logit_scale = 0.0e+00 | |
| llm_load_print_meta: n_ff = 12288 | |
| llm_load_print_meta: n_expert = 160 | |
| llm_load_print_meta: n_expert_used = 8 | |
| llm_load_print_meta: causal attn = 1 | |
| llm_load_print_meta: pooling type = 0 | |
| llm_load_print_meta: rope type = 2 | |
| llm_load_print_meta: rope scaling = linear | |
| llm_load_print_meta: freq_base_train = 1000000.0 | |
| llm_load_print_meta: freq_scale_train = 1 | |
| llm_load_print_meta: n_ctx_orig_yarn = 202752 | |
| llm_load_print_meta: rope_finetuned = unknown | |
| llm_load_print_meta: ssm_d_conv = 0 | |
| llm_load_print_meta: ssm_d_inner = 0 | |
| llm_load_print_meta: ssm_d_state = 0 | |
| llm_load_print_meta: ssm_dt_rank = 0 | |
| llm_load_print_meta: model type = 355B.A32B | |
| llm_load_print_meta: model ftype = BF16 | |
| llm_load_print_meta: model params = 358.338 B | |
| llm_load_print_meta: model size = 667.598 GiB (16.003 BPW) | |
| llm_load_print_meta: repeating layers = 664.707 GiB (16.003 BPW, 356.786 B parameters) | |
| llm_load_print_meta: general.name = GLM 4.7 | |
| print_info: vocab type = BPE | |
| print_info: n_vocab = 151552 | |
| print_info: n_merges = 318088 | |
| print_info: BOS token = 151331 '[gMASK]' | |
| print_info: EOS token = 151329 '<|endoftext|>' | |
| print_info: EOT token = 151336 '<|user|>' | |
| print_info: EOM token = 151338 '<|observation|>' | |
| print_info: UNK token = 151329 '<|endoftext|>' | |
| print_info: PAD token = 151329 '<|endoftext|>' | |
| print_info: LF token = 198 'Ċ' | |
| print_info: FIM PRE token = 151347 '<|code_prefix|>' | |
| print_info: FIM SUF token = 151349 '<|code_suffix|>' | |
| print_info: FIM MID token = 151348 '<|code_middle|>' | |
| print_info: EOG token = 151329 '<|endoftext|>' | |
| print_info: EOG token = 151336 '<|user|>' | |
| print_info: EOG token = 151338 '<|observation|>' | |
| print_info: max token length = 1024 | |
| llm_load_tensors: ggml ctx size = 0.72 MiB | |
| model has unused tensor blk.92.attn_norm.weight (size = 20480 bytes) -- ignoring | |
| model has unused tensor blk.92.attn_q.weight (size = 125829120 bytes) -- ignoring | |
| model has unused tensor blk.92.attn_k.weight (size = 10485760 bytes) -- ignoring | |
| model has unused tensor blk.92.attn_v.weight (size = 10485760 bytes) -- ignoring | |
| model has unused tensor blk.92.attn_q.bias (size = 49152 bytes) -- ignoring | |
| model has unused tensor blk.92.attn_k.bias (size = 4096 bytes) -- ignoring | |
| model has unused tensor blk.92.attn_v.bias (size = 4096 bytes) -- ignoring | |
| model has unused tensor blk.92.attn_output.weight (size = 125829120 bytes) -- ignoring | |
| model has unused tensor blk.92.attn_q_norm.weight (size = 512 bytes) -- ignoring | |
| model has unused tensor blk.92.attn_k_norm.weight (size = 512 bytes) -- ignoring | |
| model has unused tensor blk.92.post_attention_norm.weight (size = 20480 bytes) -- ignoring | |
| model has unused tensor blk.92.ffn_gate_inp.weight (size = 3276800 bytes) -- ignoring | |
| model has unused tensor blk.92.exp_probs_b.bias (size = 640 bytes) -- ignoring | |
| model has unused tensor blk.92.ffn_gate_exps.weight (size = 2516582400 bytes) -- ignoring | |
| model has unused tensor blk.92.ffn_down_exps.weight (size = 2516582400 bytes) -- ignoring | |
| model has unused tensor blk.92.ffn_up_exps.weight (size = 2516582400 bytes) -- ignoring | |
| model has unused tensor blk.92.ffn_gate_shexp.weight (size = 15728640 bytes) -- ignoring | |
| model has unused tensor blk.92.ffn_down_shexp.weight (size = 15728640 bytes) -- ignoring | |
| model has unused tensor blk.92.ffn_up_shexp.weight (size = 15728640 bytes) -- ignoring | |
| model has unused tensor blk.92.nextn.eh_proj.weight (size = 104857600 bytes) -- ignoring | |
| model has unused tensor blk.92.nextn.embed_tokens.weight (size = 1551892480 bytes) -- ignoring | |
| model has unused tensor blk.92.nextn.enorm.weight (size = 20480 bytes) -- ignoring | |
| model has unused tensor blk.92.nextn.hnorm.weight (size = 20480 bytes) -- ignoring | |
| model has unused tensor blk.92.nextn.shared_head_head.weight (size = 1551892480 bytes) -- ignoring | |
| model has unused tensor blk.92.nextn.shared_head_norm.weight (size = 20480 bytes) -- ignoring | |
| llm_load_tensors: offloading 0 repeating layers to GPU | |
| llm_load_tensors: offloaded 0/94 layers to GPU | |
| llm_load_tensors: CPU buffer size = 673051.91 MiB | |
| .................................................................................................... | |
| llama_new_context_with_model: n_ctx = 512 | |
| llama_new_context_with_model: n_batch = 512 | |
| llama_new_context_with_model: n_ubatch = 512 | |
| llama_new_context_with_model: flash_attn = 1 | |
| llama_new_context_with_model: attn_max_b = 0 | |
| llama_new_context_with_model: fused_moe = 0 | |
| llama_new_context_with_model: grouped er = 0 | |
| llama_new_context_with_model: fused_up_gate = 0 | |
| llama_new_context_with_model: fused_mmad = 0 | |
| llama_new_context_with_model: rope_cache = 0 | |
| llama_new_context_with_model: graph_reuse = 0 | |
| llama_new_context_with_model: k_cache_hadam = 0 | |
| llama_new_context_with_model: split_mode_graph_scheduling = 0 | |
| llama_new_context_with_model: ser = -1, 0 | |
| llama_new_context_with_model: freq_base = 1000000.0 | |
| llama_new_context_with_model: freq_scale = 1 | |
| llama_kv_cache_init: CPU KV buffer size = 184.00 MiB | |
| llama_new_context_with_model: KV self size = 184.00 MiB, K (f16): 92.00 MiB, V (f16): 92.00 MiB | |
| llama_new_context_with_model: CPU output buffer size = 0.58 MiB | |
| llama_new_context_with_model: CPU compute buffer size = 306.00 MiB | |
| llama_new_context_with_model: graph nodes = 4634 | |
| llama_new_context_with_model: graph splits = 1 | |
| XXXXXXXXXXXXXXXXXXXXX Setting only active experts offload | |
| system_info: n_threads = 96 (n_threads_batch = 128) / 512 | AVX = 1 | AVX_VNNI = 1 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | AVX512_BF16 = 1 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | | |
| compute_imatrix: tokenizing the input .. | |
| compute_imatrix: tokenization took 508.555 ms | |
| compute_imatrix: computing over 814 chunks with batch_size 512 | |
| compute_imatrix: 9.95 seconds per pass - ETA 2 hours 15.02 minutes | |
| ======================================= HAVE_FANCY_SIMD is defined | |
| [1]17.5129,[2]6.9568,[3]4.5205,[4]3.2674,[5]2.6460,[6]2.2556,[7]2.0217,[8]1.8697,[9]1.8579, | |
| save_imatrix: entry ' blk.73.ffn_gate_exps.weight' has partial data (98.75%) 2 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.73.ffn_up_exps.weight' has partial data (98.75%) 2 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.56.ffn_down_exps.weight' has partial data (99.38%) 1 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.56.ffn_gate_exps.weight' has partial data (99.38%) 1 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.56.ffn_up_exps.weight' has partial data (99.38%) 1 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.48.ffn_gate_exps.weight' has partial data (99.38%) 1 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.6.ffn_gate_exps.weight' has partial data (99.38%) 1 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.6.ffn_down_exps.weight' has partial data (99.38%) 1 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.6.ffn_up_exps.weight' has partial data (99.38%) 1 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.73.ffn_down_exps.weight' has partial data (98.75%) 2 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.48.ffn_down_exps.weight' has partial data (99.38%) 1 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: entry ' blk.48.ffn_up_exps.weight' has partial data (99.38%) 1 out of 160 experts are missing data Storing **but be aware** | |
| save_imatrix: stored collected data after 10 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [10]1.7776,[11]1.8889,[12]1.9858,[13]2.0575,[14]2.1264,[15]2.0255,[16]1.9435,[17]1.8890,[18]1.8325,[19]1.7753, | |
| save_imatrix: stored collected data after 20 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [20]1.7407,[21]1.6968,[22]1.6679,[23]1.6358,[24]1.6059,[25]1.5762,[26]1.6561,[27]1.7531,[28]1.8685,[29]1.8406, | |
| save_imatrix: stored collected data after 30 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [30]1.8213,[31]1.8366,[32]1.8313,[33]1.9053,[34]1.8840,[35]1.8786,[36]1.8690,[37]1.8635,[38]1.8952,[39]1.9113, | |
| save_imatrix: stored collected data after 40 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [40]1.9002,[41]1.9285,[42]1.9373,[43]1.9526,[44]1.9645,[45]1.9712,[46]1.9569,[47]1.9671,[48]1.9661,[49]1.9672, | |
| save_imatrix: stored collected data after 50 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [50]1.9573,[51]1.9761,[52]1.9892,[53]1.9766,[54]1.9847,[55]1.9872,[56]1.9924,[57]1.9852,[58]2.0341,[59]2.0846, | |
| save_imatrix: stored collected data after 60 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [60]2.1336,[61]2.1480,[62]2.1927,[63]2.2231,[64]2.2163,[65]2.2162,[66]2.2193,[67]2.2055,[68]2.2219,[69]2.2626, | |
| save_imatrix: stored collected data after 70 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [70]2.3155,[71]2.3455,[72]2.3846,[73]2.4166,[74]2.4360,[75]2.4648,[76]2.4808,[77]2.5090,[78]2.5058,[79]2.4882, | |
| save_imatrix: stored collected data after 80 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [80]2.4855,[81]2.4882,[82]2.5159,[83]2.5581,[84]2.5770,[85]2.5819,[86]2.5855,[87]2.5763,[88]2.5781,[89]2.5664, | |
| save_imatrix: stored collected data after 90 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [90]2.5561,[91]2.5523,[92]2.5356,[93]2.5154,[94]2.5440,[95]2.5928,[96]2.6132,[97]2.6158,[98]2.6236,[99]2.6440, | |
| save_imatrix: stored collected data after 100 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [100]2.6613,[101]2.6685,[102]2.6709,[103]2.7057,[104]2.7300,[105]2.7232,[106]2.7660,[107]2.8099,[108]2.8406,[109]2.8811, | |
| save_imatrix: stored collected data after 110 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [110]2.9123,[111]2.9467,[112]2.9798,[113]2.9740,[114]2.9899,[115]3.0050,[116]3.0137,[117]3.0245,[118]3.0569,[119]3.0943, | |
| save_imatrix: stored collected data after 120 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [120]3.1353,[121]3.1299,[122]3.1032,[123]3.0869,[124]3.1069,[125]3.0955,[126]3.0717,[127]3.0709,[128]3.0689,[129]3.0750, | |
| save_imatrix: stored collected data after 130 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [130]3.0827,[131]3.0998,[132]3.1160,[133]3.1226,[134]3.1614,[135]3.1798,[136]3.1540,[137]3.1290,[138]3.1061,[139]3.0821, | |
| save_imatrix: stored collected data after 140 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [140]3.0908,[141]3.1033,[142]3.1438,[143]3.1734,[144]3.1791,[145]3.2029,[146]3.2291,[147]3.2515,[148]3.2845,[149]3.3145, | |
| save_imatrix: stored collected data after 150 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [150]3.3451,[151]3.3640,[152]3.3849,[153]3.4019,[154]3.4113,[155]3.4073,[156]3.4248,[157]3.4352,[158]3.4461,[159]3.4588, | |
| save_imatrix: stored collected data after 160 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [160]3.4724,[161]3.4748,[162]3.4794,[163]3.4943,[164]3.4998,[165]3.5079,[166]3.5212,[167]3.5227,[168]3.5252,[169]3.5323, | |
| save_imatrix: stored collected data after 170 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [170]3.5418,[171]3.5468,[172]3.5522,[173]3.5591,[174]3.5774,[175]3.5892,[176]3.5948,[177]3.6013,[178]3.6183,[179]3.6066, | |
| save_imatrix: stored collected data after 180 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [180]3.6147,[181]3.6290,[182]3.6530,[183]3.6691,[184]3.6754,[185]3.6775,[186]3.6758,[187]3.6737,[188]3.6741,[189]3.6748, | |
| save_imatrix: stored collected data after 190 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [190]3.6751,[191]3.6712,[192]3.6937,[193]3.7245,[194]3.7498,[195]3.7776,[196]3.7992,[197]3.8353,[198]3.8457,[199]3.8632, | |
| save_imatrix: stored collected data after 200 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [200]3.8543,[201]3.8694,[202]3.8607,[203]3.8371,[204]3.8146,[205]3.8352,[206]3.8499,[207]3.8590,[208]3.8685,[209]3.8886, | |
| save_imatrix: stored collected data after 210 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [210]3.9044,[211]3.9209,[212]3.9405,[213]3.9567,[214]3.9581,[215]3.9352,[216]3.9111,[217]3.8873,[218]3.8636,[219]3.8407, | |
| save_imatrix: stored collected data after 220 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [220]3.8241,[221]3.8216,[222]3.8120,[223]3.8085,[224]3.7952,[225]3.7765,[226]3.7761,[227]3.7828,[228]3.8044,[229]3.8287, | |
| save_imatrix: stored collected data after 230 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [230]3.8397,[231]3.8627,[232]3.8583,[233]3.8832,[234]3.9142,[235]3.9274,[236]3.9423,[237]3.9476,[238]3.9719,[239]4.0009, | |
| save_imatrix: stored collected data after 240 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [240]3.9975,[241]4.0078,[242]4.0223,[243]4.0432,[244]4.0635,[245]4.0782,[246]4.0913,[247]4.1018,[248]4.0917,[249]4.1182, | |
| save_imatrix: stored collected data after 250 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [250]4.1322,[251]4.1512,[252]4.1620,[253]4.1670,[254]4.1736,[255]4.1769,[256]4.1893,[257]4.1941,[258]4.2055,[259]4.2207, | |
| save_imatrix: stored collected data after 260 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [260]4.2305,[261]4.2418,[262]4.2543,[263]4.2700,[264]4.2824,[265]4.2997,[266]4.2846,[267]4.2893,[268]4.2945,[269]4.3088, | |
| save_imatrix: stored collected data after 270 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [270]4.3304,[271]4.3455,[272]4.3672,[273]4.3680,[274]4.3670,[275]4.3766,[276]4.3829,[277]4.3999,[278]4.4148,[279]4.4279, | |
| save_imatrix: stored collected data after 280 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [280]4.4372,[281]4.4395,[282]4.4538,[283]4.4654,[284]4.4684,[285]4.4848,[286]4.4863,[287]4.4904,[288]4.4993,[289]4.4958, | |
| save_imatrix: stored collected data after 290 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [290]4.5076,[291]4.5134,[292]4.5196,[293]4.5372,[294]4.5508,[295]4.5653,[296]4.5830,[297]4.5879,[298]4.6079,[299]4.6212, | |
| save_imatrix: stored collected data after 300 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [300]4.6382,[301]4.6506,[302]4.6647,[303]4.6700,[304]4.6895,[305]4.6978,[306]4.7023,[307]4.7108,[308]4.7293,[309]4.7394, | |
| save_imatrix: stored collected data after 310 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [310]4.7444,[311]4.7529,[312]4.7618,[313]4.7761,[314]4.7839,[315]4.7935,[316]4.8056,[317]4.8184,[318]4.8331,[319]4.8379, | |
| save_imatrix: stored collected data after 320 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [320]4.8422,[321]4.8356,[322]4.8464,[323]4.8297,[324]4.8477,[325]4.8512,[326]4.8283,[327]4.8413,[328]4.8518,[329]4.8579, | |
| save_imatrix: stored collected data after 330 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [330]4.8640,[331]4.8633,[332]4.8671,[333]4.8863,[334]4.8834,[335]4.8949,[336]4.9110,[337]4.9204,[338]4.9253,[339]4.9127, | |
| save_imatrix: stored collected data after 340 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [340]4.9237,[341]4.9406,[342]4.9567,[343]4.9745,[344]4.9973,[345]5.0267,[346]5.0290,[347]5.0303,[348]5.0331,[349]5.0414, | |
| save_imatrix: stored collected data after 350 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [350]5.0554,[351]5.0758,[352]5.0761,[353]5.0728,[354]5.0839,[355]5.0801,[356]5.0811,[357]5.0798,[358]5.0753,[359]5.0797, | |
| save_imatrix: stored collected data after 360 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [360]5.0912,[361]5.0878,[362]5.0861,[363]5.0686,[364]5.0505,[365]5.0334,[366]5.0192,[367]4.9996,[368]4.9826,[369]4.9654, | |
| save_imatrix: stored collected data after 370 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [370]4.9512,[371]4.9353,[372]4.9188,[373]4.9057,[374]4.8921,[375]4.8736,[376]4.8610,[377]4.8467,[378]4.8301,[379]4.8157, | |
| save_imatrix: stored collected data after 380 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [380]4.8141,[381]4.7993,[382]4.7929,[383]4.7967,[384]4.7841,[385]4.7779,[386]4.7666,[387]4.7479,[388]4.7307,[389]4.7229, | |
| save_imatrix: stored collected data after 390 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [390]4.7128,[391]4.6979,[392]4.6796,[393]4.6613,[394]4.6594,[395]4.6573,[396]4.6530,[397]4.6422,[398]4.6436,[399]4.6429, | |
| save_imatrix: stored collected data after 400 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [400]4.6261,[401]4.6110,[402]4.6038,[403]4.5899,[404]4.5786,[405]4.5680,[406]4.5586,[407]4.5421,[408]4.5262,[409]4.5115, | |
| save_imatrix: stored collected data after 410 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [410]4.4991,[411]4.4877,[412]4.4820,[413]4.4730,[414]4.4690,[415]4.4643,[416]4.4624,[417]4.4571,[418]4.4519,[419]4.4374, | |
| save_imatrix: stored collected data after 420 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [420]4.4230,[421]4.4077,[422]4.3944,[423]4.3803,[424]4.3684,[425]4.3546,[426]4.3397,[427]4.3292,[428]4.3145,[429]4.3076, | |
| save_imatrix: stored collected data after 430 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [430]4.2946,[431]4.2847,[432]4.2735,[433]4.2636,[434]4.2620,[435]4.2610,[436]4.2546,[437]4.2443,[438]4.2379,[439]4.2240, | |
| save_imatrix: stored collected data after 440 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [440]4.2110,[441]4.1987,[442]4.1868,[443]4.1755,[444]4.1721,[445]4.1629,[446]4.1593,[447]4.1535,[448]4.1430,[449]4.1400, | |
| save_imatrix: stored collected data after 450 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [450]4.1326,[451]4.1249,[452]4.1137,[453]4.1065,[454]4.0994,[455]4.0910,[456]4.0787,[457]4.0669,[458]4.0547,[459]4.0430, | |
| save_imatrix: stored collected data after 460 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [460]4.0317,[461]4.0223,[462]4.0129,[463]4.0069,[464]3.9991,[465]3.9951,[466]3.9893,[467]3.9839,[468]3.9785,[469]3.9728, | |
| save_imatrix: stored collected data after 470 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [470]3.9673,[471]3.9618,[472]3.9564,[473]3.9517,[474]3.9461,[475]3.9405,[476]3.9357,[477]3.9303,[478]3.9250,[479]3.9215, | |
| save_imatrix: stored collected data after 480 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [480]3.9109,[481]3.9015,[482]3.8973,[483]3.8903,[484]3.8828,[485]3.8726,[486]3.8630,[487]3.8537,[488]3.8443,[489]3.8383, | |
| save_imatrix: stored collected data after 490 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [490]3.8310,[491]3.8243,[492]3.8204,[493]3.8151,[494]3.8084,[495]3.8004,[496]3.7998,[497]3.7966,[498]3.7917,[499]3.7900, | |
| save_imatrix: stored collected data after 500 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [500]3.7876,[501]3.7866,[502]3.7874,[503]3.7902,[504]3.7887,[505]3.7828,[506]3.7748,[507]3.7788,[508]3.7894,[509]3.7982, | |
| save_imatrix: stored collected data after 510 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [510]3.8064,[511]3.8136,[512]3.8212,[513]3.8257,[514]3.8295,[515]3.8312,[516]3.8390,[517]3.8421,[518]3.8486,[519]3.8575, | |
| save_imatrix: stored collected data after 520 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [520]3.8708,[521]3.8874,[522]3.9011,[523]3.8995,[524]3.9063,[525]3.9102,[526]3.9165,[527]3.9179,[528]3.9201,[529]3.9289, | |
| save_imatrix: stored collected data after 530 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [530]3.9341,[531]3.9355,[532]3.9425,[533]3.9482,[534]3.9554,[535]3.9553,[536]3.9550,[537]3.9558,[538]3.9602,[539]3.9650, | |
| save_imatrix: stored collected data after 540 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [540]3.9698,[541]3.9741,[542]3.9765,[543]3.9788,[544]3.9835,[545]3.9886,[546]3.9973,[547]4.0056,[548]4.0122,[549]4.0208, | |
| save_imatrix: stored collected data after 550 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [550]4.0278,[551]4.0358,[552]4.0422,[553]4.0482,[554]4.0550,[555]4.0610,[556]4.0581,[557]4.0553,[558]4.0519,[559]4.0563, | |
| save_imatrix: stored collected data after 560 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [560]4.0622,[561]4.0664,[562]4.0717,[563]4.0722,[564]4.0769,[565]4.0773,[566]4.0819,[567]4.0827,[568]4.0828,[569]4.0823, | |
| save_imatrix: stored collected data after 570 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [570]4.0830,[571]4.0859,[572]4.0823,[573]4.0797,[574]4.0752,[575]4.0715,[576]4.0642,[577]4.0590,[578]4.0525,[579]4.0453, | |
| save_imatrix: stored collected data after 580 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [580]4.0425,[581]4.0443,[582]4.0423,[583]4.0433,[584]4.0410,[585]4.0407,[586]4.0404,[587]4.0377,[588]4.0320,[589]4.0325, | |
| save_imatrix: stored collected data after 590 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [590]4.0294,[591]4.0221,[592]4.0155,[593]4.0081,[594]4.0022,[595]3.9988,[596]3.9974,[597]3.9952,[598]3.9942,[599]3.9917, | |
| save_imatrix: stored collected data after 600 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [600]3.9871,[601]3.9813,[602]3.9814,[603]3.9815,[604]3.9813,[605]3.9772,[606]3.9751,[607]3.9720,[608]3.9753,[609]3.9744, | |
| save_imatrix: stored collected data after 610 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [610]3.9720,[611]3.9726,[612]3.9723,[613]3.9676,[614]3.9607,[615]3.9530,[616]3.9455,[617]3.9375,[618]3.9301,[619]3.9224, | |
| save_imatrix: stored collected data after 620 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [620]3.9147,[621]3.9061,[622]3.8977,[623]3.8901,[624]3.8827,[625]3.8750,[626]3.8686,[627]3.8608,[628]3.8540,[629]3.8483, | |
| save_imatrix: stored collected data after 630 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [630]3.8414,[631]3.8345,[632]3.8297,[633]3.8220,[634]3.8178,[635]3.8159,[636]3.8125,[637]3.8052,[638]3.7995,[639]3.7934, | |
| save_imatrix: stored collected data after 640 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [640]3.7862,[641]3.7807,[642]3.7742,[643]3.7684,[644]3.7622,[645]3.7555,[646]3.7488,[647]3.7428,[648]3.7423,[649]3.7357, | |
| save_imatrix: stored collected data after 650 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [650]3.7289,[651]3.7222,[652]3.7158,[653]3.7091,[654]3.7022,[655]3.6956,[656]3.6892,[657]3.6834,[658]3.6769,[659]3.6795, | |
| save_imatrix: stored collected data after 660 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [660]3.6798,[661]3.6828,[662]3.6807,[663]3.6746,[664]3.6705,[665]3.6650,[666]3.6584,[667]3.6531,[668]3.6477,[669]3.6427, | |
| save_imatrix: stored collected data after 670 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [670]3.6377,[671]3.6320,[672]3.6260,[673]3.6203,[674]3.6165,[675]3.6115,[676]3.6057,[677]3.6006,[678]3.5948,[679]3.5888, | |
| save_imatrix: stored collected data after 680 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [680]3.5861,[681]3.5802,[682]3.5752,[683]3.5704,[684]3.5649,[685]3.5604,[686]3.5584,[687]3.5571,[688]3.5532,[689]3.5485, | |
| save_imatrix: stored collected data after 690 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [690]3.5423,[691]3.5359,[692]3.5305,[693]3.5249,[694]3.5211,[695]3.5185,[696]3.5168,[697]3.5141,[698]3.5125,[699]3.5101, | |
| save_imatrix: stored collected data after 700 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [700]3.5082,[701]3.5068,[702]3.5052,[703]3.5033,[704]3.5014,[705]3.4998,[706]3.4983,[707]3.4959,[708]3.4946,[709]3.4925, | |
| save_imatrix: stored collected data after 710 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [710]3.4907,[711]3.4886,[712]3.4894,[713]3.4891,[714]3.4893,[715]3.4904,[716]3.4915,[717]3.4923,[718]3.4931,[719]3.4948, | |
| save_imatrix: stored collected data after 720 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [720]3.4969,[721]3.4973,[722]3.4981,[723]3.4991,[724]3.5006,[725]3.5017,[726]3.5034,[727]3.5048,[728]3.5068,[729]3.5068, | |
| save_imatrix: stored collected data after 730 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [730]3.5070,[731]3.5082,[732]3.5111,[733]3.5122,[734]3.5126,[735]3.5127,[736]3.5141,[737]3.5162,[738]3.5169,[739]3.5198, | |
| save_imatrix: stored collected data after 740 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [740]3.5214,[741]3.5233,[742]3.5248,[743]3.5255,[744]3.5255,[745]3.5267,[746]3.5283,[747]3.5298,[748]3.5312,[749]3.5323, | |
| save_imatrix: stored collected data after 750 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [750]3.5335,[751]3.5345,[752]3.5365,[753]3.5398,[754]3.5405,[755]3.5417,[756]3.5434,[757]3.5449,[758]3.5457,[759]3.5472, | |
| save_imatrix: stored collected data after 760 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [760]3.5482,[761]3.5489,[762]3.5507,[763]3.5511,[764]3.5530,[765]3.5540,[766]3.5556,[767]3.5563,[768]3.5573,[769]3.5577, | |
| save_imatrix: stored collected data after 770 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [770]3.5588,[771]3.5610,[772]3.5617,[773]3.5619,[774]3.5626,[775]3.5646,[776]3.5655,[777]3.5679,[778]3.5679,[779]3.5693, | |
| save_imatrix: stored collected data after 780 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [780]3.5708,[781]3.5729,[782]3.5750,[783]3.5778,[784]3.5781,[785]3.5787,[786]3.5794,[787]3.5812,[788]3.5814,[789]3.5837, | |
| save_imatrix: stored collected data after 790 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [790]3.5849,[791]3.5861,[792]3.5863,[793]3.5874,[794]3.5896,[795]3.5911,[796]3.5914,[797]3.5930,[798]3.5942,[799]3.5979, | |
| save_imatrix: stored collected data after 800 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [800]3.5984,[801]3.5983,[802]3.6000,[803]3.6018,[804]3.6027,[805]3.6036,[806]3.6041,[807]3.6050,[808]3.6054,[809]3.6062, | |
| save_imatrix: stored collected data after 810 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| [810]3.6083,[811]3.6108,[812]3.6119,[813]3.6131,[814]3.6137, | |
| save_imatrix: stored collected data after 814 chunks in /mnt/data/models/ubergarm/GLM-4.7-GGUF/imatrix-GLM-4.7-BF16.dat | |
| Final estimate: PPL = 3.6137 +/- 0.01805 | |
| ======================== sorted layer importances | |
| 0: Layer 0, <cos_sim> = 0.433589 | |
| 1: Layer 2, <cos_sim> = 0.752289 | |
| 2: Layer 1, <cos_sim> = 0.764358 | |
| 3: Layer 3, <cos_sim> = 0.861103 | |
| 4: Layer 4, <cos_sim> = 0.90387 | |
| 5: Layer 32, <cos_sim> = 0.905589 | |
| 6: Layer 6, <cos_sim> = 0.912358 | |
| 7: Layer 37, <cos_sim> = 0.913118 | |
| 8: Layer 39, <cos_sim> = 0.913941 | |
| 9: Layer 31, <cos_sim> = 0.914878 | |
| 10: Layer 23, <cos_sim> = 0.915726 | |
| 11: Layer 91, <cos_sim> = 0.915909 | |
| 12: Layer 41, <cos_sim> = 0.917222 | |
| 13: Layer 40, <cos_sim> = 0.918507 | |
| 14: Layer 33, <cos_sim> = 0.918549 | |
| 15: Layer 29, <cos_sim> = 0.919203 | |
| 16: Layer 30, <cos_sim> = 0.919353 | |
| 17: Layer 28, <cos_sim> = 0.921385 | |
| 18: Layer 38, <cos_sim> = 0.921396 | |
| 19: Layer 24, <cos_sim> = 0.922245 | |
| 20: Layer 34, <cos_sim> = 0.922372 | |
| 21: Layer 22, <cos_sim> = 0.922432 | |
| 22: Layer 26, <cos_sim> = 0.924714 | |
| 23: Layer 36, <cos_sim> = 0.924901 | |
| 24: Layer 14, <cos_sim> = 0.925139 | |
| 25: Layer 25, <cos_sim> = 0.9268 | |
| 26: Layer 13, <cos_sim> = 0.92694 | |
| 27: Layer 35, <cos_sim> = 0.927297 | |
| 28: Layer 10, <cos_sim> = 0.927834 | |
| 29: Layer 27, <cos_sim> = 0.928177 | |
| 30: Layer 11, <cos_sim> = 0.929866 | |
| 31: Layer 21, <cos_sim> = 0.929894 | |
| 32: Layer 85, <cos_sim> = 0.93049 | |
| 33: Layer 7, <cos_sim> = 0.930774 | |
| 34: Layer 84, <cos_sim> = 0.932103 | |
| 35: Layer 8, <cos_sim> = 0.933102 | |
| 36: Layer 9, <cos_sim> = 0.935479 | |
| 37: Layer 42, <cos_sim> = 0.935862 | |
| 38: Layer 12, <cos_sim> = 0.936215 | |
| 39: Layer 5, <cos_sim> = 0.941695 | |
| 40: Layer 43, <cos_sim> = 0.943382 | |
| 41: Layer 86, <cos_sim> = 0.947319 | |
| 42: Layer 15, <cos_sim> = 0.948505 | |
| 43: Layer 20, <cos_sim> = 0.948549 | |
| 44: Layer 18, <cos_sim> = 0.951088 | |
| 45: Layer 44, <cos_sim> = 0.952598 | |
| 46: Layer 83, <cos_sim> = 0.952599 | |
| 47: Layer 19, <cos_sim> = 0.952615 | |
| 48: Layer 45, <cos_sim> = 0.953287 | |
| 49: Layer 17, <cos_sim> = 0.956447 | |
| 50: Layer 80, <cos_sim> = 0.957907 | |
| 51: Layer 16, <cos_sim> = 0.957981 | |
| 52: Layer 46, <cos_sim> = 0.958118 | |
| 53: Layer 81, <cos_sim> = 0.959244 | |
| 54: Layer 87, <cos_sim> = 0.959352 | |
| 55: Layer 90, <cos_sim> = 0.960285 | |
| 56: Layer 82, <cos_sim> = 0.961087 | |
| 57: Layer 47, <cos_sim> = 0.961475 | |
| 58: Layer 89, <cos_sim> = 0.962276 | |
| 59: Layer 88, <cos_sim> = 0.963196 | |
| 60: Layer 79, <cos_sim> = 0.963523 | |
| 61: Layer 48, <cos_sim> = 0.963567 | |
| 62: Layer 50, <cos_sim> = 0.964597 | |
| 63: Layer 49, <cos_sim> = 0.965508 | |
| 64: Layer 51, <cos_sim> = 0.965609 | |
| 65: Layer 52, <cos_sim> = 0.967696 | |
| 66: Layer 54, <cos_sim> = 0.968009 | |
| 67: Layer 53, <cos_sim> = 0.970224 | |
| 68: Layer 76, <cos_sim> = 0.970396 | |
| 69: Layer 78, <cos_sim> = 0.971591 | |
| 70: Layer 55, <cos_sim> = 0.971771 | |
| 71: Layer 75, <cos_sim> = 0.973436 | |
| 72: Layer 77, <cos_sim> = 0.975951 | |
| 73: Layer 58, <cos_sim> = 0.978094 | |
| 74: Layer 56, <cos_sim> = 0.978404 | |
| 75: Layer 57, <cos_sim> = 0.979015 | |
| 76: Layer 59, <cos_sim> = 0.979639 | |
| 77: Layer 73, <cos_sim> = 0.980629 | |
| 78: Layer 67, <cos_sim> = 0.981126 | |
| 79: Layer 66, <cos_sim> = 0.981658 | |
| 80: Layer 72, <cos_sim> = 0.981951 | |
| 81: Layer 65, <cos_sim> = 0.981978 | |
| 82: Layer 61, <cos_sim> = 0.982014 | |
| 83: Layer 68, <cos_sim> = 0.982152 | |
| 84: Layer 74, <cos_sim> = 0.982164 | |
| 85: Layer 60, <cos_sim> = 0.982302 | |
| 86: Layer 71, <cos_sim> = 0.982914 | |
| 87: Layer 63, <cos_sim> = 0.983344 | |
| 88: Layer 70, <cos_sim> = 0.983749 | |
| 89: Layer 64, <cos_sim> = 0.984071 | |
| 90: Layer 69, <cos_sim> = 0.984258 | |
| 91: Layer 62, <cos_sim> = 0.984467 | |
| ======================== sorted attention importances | |
| 0: Layer 0, <cos_sim> = 0.335289 | |
| 1: Layer 1, <cos_sim> = 0.552763 | |
| 2: Layer 2, <cos_sim> = 0.637396 | |
| 3: Layer 3, <cos_sim> = 0.816339 | |
| 4: Layer 7, <cos_sim> = 0.824544 | |
| 5: Layer 13, <cos_sim> = 0.850178 | |
| 6: Layer 6, <cos_sim> = 0.850298 | |
| 7: Layer 4, <cos_sim> = 0.851804 | |
| 8: Layer 9, <cos_sim> = 0.859275 | |
| 9: Layer 8, <cos_sim> = 0.866695 | |
| 10: Layer 12, <cos_sim> = 0.874505 | |
| 11: Layer 15, <cos_sim> = 0.876165 | |
| 12: Layer 5, <cos_sim> = 0.876507 | |
| 13: Layer 10, <cos_sim> = 0.87806 | |
| 14: Layer 11, <cos_sim> = 0.880676 | |
| 15: Layer 16, <cos_sim> = 0.893902 | |
| 16: Layer 17, <cos_sim> = 0.899423 | |
| 17: Layer 21, <cos_sim> = 0.900672 | |
| 18: Layer 14, <cos_sim> = 0.9032 | |
| 19: Layer 19, <cos_sim> = 0.909055 | |
| 20: Layer 20, <cos_sim> = 0.911488 | |
| 21: Layer 18, <cos_sim> = 0.917251 | |
| 22: Layer 23, <cos_sim> = 0.919361 | |
| 23: Layer 22, <cos_sim> = 0.928206 | |
| 24: Layer 24, <cos_sim> = 0.932381 | |
| 25: Layer 25, <cos_sim> = 0.936273 | |
| 26: Layer 32, <cos_sim> = 0.938645 | |
| 27: Layer 28, <cos_sim> = 0.941543 | |
| 28: Layer 26, <cos_sim> = 0.942651 | |
| 29: Layer 33, <cos_sim> = 0.943323 | |
| 30: Layer 27, <cos_sim> = 0.943763 | |
| 31: Layer 37, <cos_sim> = 0.944613 | |
| 32: Layer 31, <cos_sim> = 0.945652 | |
| 33: Layer 30, <cos_sim> = 0.946387 | |
| 34: Layer 38, <cos_sim> = 0.948997 | |
| 35: Layer 39, <cos_sim> = 0.94954 | |
| 36: Layer 35, <cos_sim> = 0.950607 | |
| 37: Layer 41, <cos_sim> = 0.951778 | |
| 38: Layer 34, <cos_sim> = 0.952551 | |
| 39: Layer 40, <cos_sim> = 0.95284 | |
| 40: Layer 29, <cos_sim> = 0.952981 | |
| 41: Layer 42, <cos_sim> = 0.954776 | |
| 42: Layer 36, <cos_sim> = 0.958211 | |
| 43: Layer 85, <cos_sim> = 0.963066 | |
| 44: Layer 43, <cos_sim> = 0.963722 | |
| 45: Layer 44, <cos_sim> = 0.964977 | |
| 46: Layer 45, <cos_sim> = 0.966557 | |
| 47: Layer 46, <cos_sim> = 0.969251 | |
| 48: Layer 84, <cos_sim> = 0.971393 | |
| 49: Layer 86, <cos_sim> = 0.971928 | |
| 50: Layer 51, <cos_sim> = 0.973333 | |
| 51: Layer 52, <cos_sim> = 0.974347 | |
| 52: Layer 83, <cos_sim> = 0.974803 | |
| 53: Layer 50, <cos_sim> = 0.977621 | |
| 54: Layer 48, <cos_sim> = 0.977849 | |
| 55: Layer 47, <cos_sim> = 0.97789 | |
| 56: Layer 81, <cos_sim> = 0.978345 | |
| 57: Layer 82, <cos_sim> = 0.978486 | |
| 58: Layer 49, <cos_sim> = 0.978655 | |
| 59: Layer 80, <cos_sim> = 0.97866 | |
| 60: Layer 53, <cos_sim> = 0.979166 | |
| 61: Layer 91, <cos_sim> = 0.98049 | |
| 62: Layer 58, <cos_sim> = 0.981312 | |
| 63: Layer 54, <cos_sim> = 0.981736 | |
| 64: Layer 87, <cos_sim> = 0.982023 | |
| 65: Layer 79, <cos_sim> = 0.982483 | |
| 66: Layer 78, <cos_sim> = 0.983622 | |
| 67: Layer 88, <cos_sim> = 0.983653 | |
| 68: Layer 90, <cos_sim> = 0.985642 | |
| 69: Layer 61, <cos_sim> = 0.986197 | |
| 70: Layer 89, <cos_sim> = 0.986293 | |
| 71: Layer 68, <cos_sim> = 0.986564 | |
| 72: Layer 59, <cos_sim> = 0.986572 | |
| 73: Layer 73, <cos_sim> = 0.98676 | |
| 74: Layer 71, <cos_sim> = 0.986905 | |
| 75: Layer 55, <cos_sim> = 0.986992 | |
| 76: Layer 72, <cos_sim> = 0.987429 | |
| 77: Layer 76, <cos_sim> = 0.987882 | |
| 78: Layer 57, <cos_sim> = 0.988337 | |
| 79: Layer 56, <cos_sim> = 0.988355 | |
| 80: Layer 77, <cos_sim> = 0.98847 | |
| 81: Layer 67, <cos_sim> = 0.988501 | |
| 82: Layer 65, <cos_sim> = 0.98852 | |
| 83: Layer 70, <cos_sim> = 0.988926 | |
| 84: Layer 74, <cos_sim> = 0.988971 | |
| 85: Layer 64, <cos_sim> = 0.988973 | |
| 86: Layer 63, <cos_sim> = 0.989051 | |
| 87: Layer 66, <cos_sim> = 0.989456 | |
| 88: Layer 60, <cos_sim> = 0.989791 | |
| 89: Layer 69, <cos_sim> = 0.99087 | |
| 90: Layer 75, <cos_sim> = 0.991036 | |
| 91: Layer 62, <cos_sim> = 0.991942 | |
| ======================== sorted ffn importances | |
| 0: Layer 0, <cos_sim> = 0.584305 | |
| 1: Layer 1, <cos_sim> = 0.599857 | |
| 2: Layer 2, <cos_sim> = 0.734115 | |
| 3: Layer 6, <cos_sim> = 0.807659 | |
| 4: Layer 3, <cos_sim> = 0.823881 | |
| 5: Layer 8, <cos_sim> = 0.855655 | |
| 6: Layer 11, <cos_sim> = 0.855686 | |
| 7: Layer 4, <cos_sim> = 0.858089 | |
| 8: Layer 14, <cos_sim> = 0.858127 | |
| 9: Layer 12, <cos_sim> = 0.860683 | |
| 10: Layer 5, <cos_sim> = 0.864949 | |
| 11: Layer 7, <cos_sim> = 0.867606 | |
| 12: Layer 9, <cos_sim> = 0.883365 | |
| 13: Layer 10, <cos_sim> = 0.884968 | |
| 14: Layer 15, <cos_sim> = 0.885658 | |
| 15: Layer 16, <cos_sim> = 0.887954 | |
| 16: Layer 20, <cos_sim> = 0.892895 | |
| 17: Layer 18, <cos_sim> = 0.90077 | |
| 18: Layer 19, <cos_sim> = 0.901247 | |
| 19: Layer 13, <cos_sim> = 0.902837 | |
| 20: Layer 24, <cos_sim> = 0.914728 | |
| 21: Layer 22, <cos_sim> = 0.91663 | |
| 22: Layer 25, <cos_sim> = 0.91686 | |
| 23: Layer 17, <cos_sim> = 0.91982 | |
| 24: Layer 26, <cos_sim> = 0.920503 | |
| 25: Layer 23, <cos_sim> = 0.921116 | |
| 26: Layer 27, <cos_sim> = 0.924545 | |
| 27: Layer 29, <cos_sim> = 0.92818 | |
| 28: Layer 32, <cos_sim> = 0.931219 | |
| 29: Layer 21, <cos_sim> = 0.931957 | |
| 30: Layer 31, <cos_sim> = 0.931987 | |
| 31: Layer 28, <cos_sim> = 0.933451 | |
| 32: Layer 30, <cos_sim> = 0.934623 | |
| 33: Layer 34, <cos_sim> = 0.935862 | |
| 34: Layer 37, <cos_sim> = 0.93849 | |
| 35: Layer 36, <cos_sim> = 0.939261 | |
| 36: Layer 33, <cos_sim> = 0.94047 | |
| 37: Layer 39, <cos_sim> = 0.942833 | |
| 38: Layer 40, <cos_sim> = 0.943535 | |
| 39: Layer 35, <cos_sim> = 0.943962 | |
| 40: Layer 41, <cos_sim> = 0.944572 | |
| 41: Layer 91, <cos_sim> = 0.944611 | |
| 42: Layer 38, <cos_sim> = 0.94701 | |
| 43: Layer 43, <cos_sim> = 0.951876 | |
| 44: Layer 42, <cos_sim> = 0.953462 | |
| 45: Layer 44, <cos_sim> = 0.954221 | |
| 46: Layer 45, <cos_sim> = 0.954828 | |
| 47: Layer 84, <cos_sim> = 0.960194 | |
| 48: Layer 46, <cos_sim> = 0.962422 | |
| 49: Layer 47, <cos_sim> = 0.963472 | |
| 50: Layer 50, <cos_sim> = 0.963841 | |
| 51: Layer 48, <cos_sim> = 0.964882 | |
| 52: Layer 51, <cos_sim> = 0.96498 | |
| 53: Layer 49, <cos_sim> = 0.965125 | |
| 54: Layer 85, <cos_sim> = 0.965745 | |
| 55: Layer 90, <cos_sim> = 0.966198 | |
| 56: Layer 52, <cos_sim> = 0.968709 | |
| 57: Layer 89, <cos_sim> = 0.969302 | |
| 58: Layer 86, <cos_sim> = 0.970209 | |
| 59: Layer 79, <cos_sim> = 0.971392 | |
| 60: Layer 80, <cos_sim> = 0.97181 | |
| 61: Layer 83, <cos_sim> = 0.971817 | |
| 62: Layer 53, <cos_sim> = 0.972442 | |
| 63: Layer 81, <cos_sim> = 0.972559 | |
| 64: Layer 87, <cos_sim> = 0.973106 | |
| 65: Layer 78, <cos_sim> = 0.973454 | |
| 66: Layer 57, <cos_sim> = 0.973742 | |
| 67: Layer 77, <cos_sim> = 0.97382 | |
| 68: Layer 82, <cos_sim> = 0.974303 | |
| 69: Layer 55, <cos_sim> = 0.974649 | |
| 70: Layer 54, <cos_sim> = 0.974867 | |
| 71: Layer 76, <cos_sim> = 0.975321 | |
| 72: Layer 75, <cos_sim> = 0.975472 | |
| 73: Layer 88, <cos_sim> = 0.975633 | |
| 74: Layer 58, <cos_sim> = 0.976417 | |
| 75: Layer 56, <cos_sim> = 0.976436 | |
| 76: Layer 60, <cos_sim> = 0.976607 | |
| 77: Layer 73, <cos_sim> = 0.977296 | |
| 78: Layer 72, <cos_sim> = 0.977447 | |
| 79: Layer 65, <cos_sim> = 0.977744 | |
| 80: Layer 67, <cos_sim> = 0.977822 | |
| 81: Layer 70, <cos_sim> = 0.977891 | |
| 82: Layer 59, <cos_sim> = 0.978032 | |
| 83: Layer 71, <cos_sim> = 0.978203 | |
| 84: Layer 69, <cos_sim> = 0.97839 | |
| 85: Layer 64, <cos_sim> = 0.978551 | |
| 86: Layer 66, <cos_sim> = 0.978619 | |
| 87: Layer 63, <cos_sim> = 0.97875 | |
| 88: Layer 74, <cos_sim> = 0.979117 | |
| 89: Layer 62, <cos_sim> = 0.979471 | |
| 90: Layer 68, <cos_sim> = 0.979636 | |
| 91: Layer 61, <cos_sim> = 0.980855 | |
| llama_print_timings: load time = 195855.60 ms | |
| llama_print_timings: sample time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second) | |
| llama_print_timings: prompt eval time = 7668240.55 ms / 416768 tokens ( 18.40 ms per token, 54.35 tokens per second) | |
| llama_print_timings: eval time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second) | |
| llama_print_timings: total time = 7872041.86 ms / 416769 tokens | |