Text Generation
Transformers
Safetensors
qwen2
code
software-engineering
fim
conversational
text-generation-inference
Instructions to use TIGER-Lab/FIM-Mid-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TIGER-Lab/FIM-Mid-14B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TIGER-Lab/FIM-Mid-14B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TIGER-Lab/FIM-Mid-14B") model = AutoModelForCausalLM.from_pretrained("TIGER-Lab/FIM-Mid-14B", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TIGER-Lab/FIM-Mid-14B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TIGER-Lab/FIM-Mid-14B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TIGER-Lab/FIM-Mid-14B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/TIGER-Lab/FIM-Mid-14B
- SGLang
How to use TIGER-Lab/FIM-Mid-14B 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 "TIGER-Lab/FIM-Mid-14B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TIGER-Lab/FIM-Mid-14B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "TIGER-Lab/FIM-Mid-14B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TIGER-Lab/FIM-Mid-14B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use TIGER-Lab/FIM-Mid-14B with Docker Model Runner:
docker model run hf.co/TIGER-Lab/FIM-Mid-14B
Add files using upload-large-folder tool
Browse files- .gitattributes +1 -0
- README.md +44 -0
- chat_template.jinja +54 -0
- config.json +82 -0
- generation_config.json +13 -0
- model.safetensors +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +30 -0
.gitattributes
CHANGED
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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base_model:
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- Qwen/Qwen2.5-Coder-14B-Instruct
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tags:
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- code
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- software-engineering
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- fim
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---
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# FIM-Mid-14B
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**FIM-Mid-14B** is the mid-trained checkpoint of the FIM 14B pipeline: `Qwen2.5-Coder-14B-Instruct` after FIM mid-training, **before** agent post-training. Post-training this checkpoint on R2E-Gym agent trajectories produces [TIGER-Lab/FIM-14B](https://huggingface.co/TIGER-Lab/FIM-14B).
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## Model
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Local path: `models/FIM-Mid-14B/` (checkpoints are gitignored; do not commit them).
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- Base model: `Qwen/Qwen2.5-Coder-14B-Instruct`
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- FIM mid-training: `train/FIM_Midtrain_14B.yaml` (AdamW, lr `1.0e-5`, cosine schedule, warmup ratio `0.1`, weight decay `0.05`, one epoch, sequence length `32768`, bf16)
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- Post-training: none — see [TIGER-Lab/FIM-14B](https://huggingface.co/TIGER-Lab/FIM-14B) for the post-trained agent model
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## Serve with vLLM
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A standard Qwen2.5 checkpoint; no overrides needed at its native 32768 context:
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```bash
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CUDA_VISIBLE_DEVICES=0 \
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python -m vllm.entrypoints.openai.api_server \
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--model models/FIM-Mid-14B \
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--served-model-name FIM-Mid-14B \
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--host 127.0.0.1 \
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--port 8400 \
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--tensor-parallel-size 1 \
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--max-model-len 32768 \
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--gpu-memory-utilization 0.9 \
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> vllm_fim_mid14b.log 2>&1 &
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```
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## Post-training
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To reproduce FIM-14B, run R2E-Gym trajectory SFT from this checkpoint (LLaMA-Factory, full fine-tuning, lr `1.0e-5`, 2 epochs, cutoff 32768).
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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| 50 |
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{%- endif %}
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| 51 |
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{%- endfor %}
|
| 52 |
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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config.json
ADDED
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{
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| 2 |
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"architectures": [
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| 3 |
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"Qwen2ForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_dropout": 0.0,
|
| 6 |
+
"bos_token_id": null,
|
| 7 |
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"dtype": "bfloat16",
|
| 8 |
+
"eos_token_id": 151645,
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| 9 |
+
"hidden_act": "silu",
|
| 10 |
+
"hidden_size": 5120,
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| 11 |
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"initializer_range": 0.02,
|
| 12 |
+
"intermediate_size": 13824,
|
| 13 |
+
"layer_types": [
|
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"full_attention",
|
| 15 |
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"full_attention",
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"full_attention",
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| 17 |
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"full_attention",
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| 18 |
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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| 23 |
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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| 33 |
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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| 37 |
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"full_attention",
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| 38 |
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"full_attention",
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| 39 |
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"full_attention",
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| 40 |
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"full_attention",
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| 41 |
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"full_attention",
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| 42 |
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"full_attention",
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| 43 |
+
"full_attention",
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| 44 |
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"full_attention",
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| 45 |
+
"full_attention",
|
| 46 |
+
"full_attention",
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| 47 |
+
"full_attention",
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| 48 |
+
"full_attention",
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| 49 |
+
"full_attention",
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| 50 |
+
"full_attention",
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| 51 |
+
"full_attention",
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| 52 |
+
"full_attention",
|
| 53 |
+
"full_attention",
|
| 54 |
+
"full_attention",
|
| 55 |
+
"full_attention",
|
| 56 |
+
"full_attention",
|
| 57 |
+
"full_attention",
|
| 58 |
+
"full_attention",
|
| 59 |
+
"full_attention",
|
| 60 |
+
"full_attention",
|
| 61 |
+
"full_attention"
|
| 62 |
+
],
|
| 63 |
+
"max_position_embeddings": 32768,
|
| 64 |
+
"max_window_layers": 48,
|
| 65 |
+
"model_type": "qwen2",
|
| 66 |
+
"num_attention_heads": 40,
|
| 67 |
+
"num_hidden_layers": 48,
|
| 68 |
+
"num_key_value_heads": 8,
|
| 69 |
+
"pad_token_id": 151643,
|
| 70 |
+
"rms_norm_eps": 1e-06,
|
| 71 |
+
"rope_theta": 1000000.0,
|
| 72 |
+
"rope_parameters": {
|
| 73 |
+
"rope_theta": 1000000.0,
|
| 74 |
+
"rope_type": "default"
|
| 75 |
+
},
|
| 76 |
+
"sliding_window": null,
|
| 77 |
+
"tie_word_embeddings": false,
|
| 78 |
+
"transformers_version": "5.0.0",
|
| 79 |
+
"use_cache": false,
|
| 80 |
+
"use_sliding_window": false,
|
| 81 |
+
"vocab_size": 152064
|
| 82 |
+
}
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generation_config.json
ADDED
|
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{
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| 2 |
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"do_sample": true,
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| 3 |
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"eos_token_id": [
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| 4 |
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151645,
|
| 5 |
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151643
|
| 6 |
+
],
|
| 7 |
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"pad_token_id": 151643,
|
| 8 |
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"repetition_penalty": 1.05,
|
| 9 |
+
"temperature": 0.7,
|
| 10 |
+
"top_k": 20,
|
| 11 |
+
"top_p": 0.8,
|
| 12 |
+
"transformers_version": "5.0.0"
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| 13 |
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}
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model.safetensors
ADDED
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version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1c4209cee5b31280aa2b5f0fb1ab0186f912455ed2b06833d23800a96e815413
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| 3 |
+
size 29540134824
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tokenizer.json
ADDED
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
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| 3 |
+
size 11421892
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tokenizer_config.json
ADDED
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| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": null,
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"eos_token": "<|im_end|>",
|
| 7 |
+
"errors": "replace",
|
| 8 |
+
"extra_special_tokens": [
|
| 9 |
+
"<|im_start|>",
|
| 10 |
+
"<|im_end|>",
|
| 11 |
+
"<|object_ref_start|>",
|
| 12 |
+
"<|object_ref_end|>",
|
| 13 |
+
"<|box_start|>",
|
| 14 |
+
"<|box_end|>",
|
| 15 |
+
"<|quad_start|>",
|
| 16 |
+
"<|quad_end|>",
|
| 17 |
+
"<|vision_start|>",
|
| 18 |
+
"<|vision_end|>",
|
| 19 |
+
"<|vision_pad|>",
|
| 20 |
+
"<|image_pad|>",
|
| 21 |
+
"<|video_pad|>"
|
| 22 |
+
],
|
| 23 |
+
"is_local": true,
|
| 24 |
+
"model_max_length": 32768,
|
| 25 |
+
"pad_token": "<|endoftext|>",
|
| 26 |
+
"padding_side": "right",
|
| 27 |
+
"split_special_tokens": false,
|
| 28 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 29 |
+
"unk_token": null
|
| 30 |
+
}
|