Text Generation
Safetensors
PyTorch
English
olmo2
causal-lm
olmo
autoround
intel-autoround
gptq
auto-gptq
autogptq
woq
intel
8-bit precision
Instructions to use fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- vLLM
How to use fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym
- SGLang
How to use fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym with Docker Model Runner:
docker model run hf.co/fbaldassarri/allenai_OLMo-2-1124-13B-autogptq-int8-gs128-asym
| { | |
| "_name_or_path": "allenai/OLMo-2-1124-13B", | |
| "architectures": [ | |
| "Olmo2ForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "eos_token_id": 100257, | |
| "hidden_act": "silu", | |
| "hidden_size": 5120, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 13824, | |
| "max_position_embeddings": 4096, | |
| "model_type": "olmo2", | |
| "num_attention_heads": 40, | |
| "num_hidden_layers": 40, | |
| "num_key_value_heads": 40, | |
| "pad_token_id": 100277, | |
| "quantization_config": { | |
| "amp": false, | |
| "autoround_version": "0.4.5", | |
| "batch_size": 4, | |
| "bits": 8, | |
| "damp_percent": 0.01, | |
| "data_type": "int", | |
| "desc_act": false, | |
| "enable_minmax_tuning": true, | |
| "enable_norm_bias_tuning": false, | |
| "enable_quanted_input": true, | |
| "gradient_accumulate_steps": 1, | |
| "group_size": 128, | |
| "iters": 200, | |
| "low_gpu_mem_usage": false, | |
| "lr": 0.005, | |
| "minmax_lr": 0.005, | |
| "nsamples": 128, | |
| "quant_method": "gptq", | |
| "scale_dtype": "torch.float16", | |
| "seqlen": 512, | |
| "sym": false, | |
| "to_quant_block_names": null, | |
| "true_sequential": false | |
| }, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 500000, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.48.3", | |
| "use_cache": true, | |
| "vocab_size": 100352 | |
| } | |