初始化项目，由ModelHub XC社区提供模型
Model: TIGER-Lab/FIM-7B Source: Original Platform
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109
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-7B-Instruct
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datasets:
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- TIGER-Lab/FIM-Midtraining-400K
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- R2E-Gym/R2EGym-SFT-Trajectories
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tags:
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- code
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- software-engineering
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- agent
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---
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# FIM-7B
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[📄 Paper](https://arxiv.org/abs/2607.12463) · [💻 GitHub](https://github.com/TIGER-AI-Lab/FIM-Midtraining) · [🤗 Dataset](https://huggingface.co/datasets/TIGER-Lab/FIM-Midtraining-400K) · [🤗 Collection](https://huggingface.co/collections/TIGER-Lab/fim-midtraining)
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**FIM-7B** is the 7B coding-agent model of *"Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models"*: `Qwen2.5-Coder-7B-Instruct`, mid-trained on function-aware FIM data, then post-trained on R2E-Gym agent trajectories with the upstream recipe unmodified. The mid-training stage is the only difference from a standard R2E-Gym reproduction — and it is worth **+2.8 points on SWE-Bench-Verified and +3.7 on SWE-Bench-Lite**.
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## Training pipeline
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- **Base model**: [`Qwen/Qwen2.5-Coder-7B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct)
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- **FIM mid-training**: [`midtraining/configs/fim_midtrain.yaml`](https://github.com/TIGER-AI-Lab/FIM-Midtraining/blob/main/midtraining/configs/fim_midtrain.yaml) on [TIGER-Lab/FIM-Midtraining-400K](https://huggingface.co/datasets/TIGER-Lab/FIM-Midtraining-400K) (as-run copy: [`FIM_Midtrain_7B.yaml`](https://github.com/TIGER-AI-Lab/FIM-Midtraining/blob/main/midtraining/configs/FIM_Midtrain_7B.yaml)) → intermediate checkpoint released as [TIGER-Lab/FIM-Mid-7B](https://huggingface.co/TIGER-Lab/FIM-Mid-7B)
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- **Post-training**: SFT on R2E-Gym agent trajectories — [`posttraining/r2egym/`](https://github.com/TIGER-AI-Lab/FIM-Midtraining/tree/main/posttraining/r2egym) (as-run copy: [`FIM_Posttrain_7B.yaml`](https://github.com/TIGER-AI-Lab/FIM-Midtraining/blob/main/posttraining/r2egym/FIM_Posttrain_7B.yaml))
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## Results
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Means over three evaluation seeds, identical harness for both arms (paper Table 1):
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| Setting | SWE-Bench-Verified | SWE-Bench-Lite |
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|---|---|---|
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| Qwen2.5-Coder-7B-Instruct + R2E-Gym (reproduced) | 15.00 | 11.33 |
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| **FIM-7B (+ FIM mid-training)** | **17.80** | **15.00** |
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| Δ | +2.80 | +3.67 |
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## Evaluate on SWE-Bench Verified
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FIM-7B is evaluated with the **R2E-Gym agent scaffold** (fixed by its post-training pipeline). The complete pinned walkthrough lives at [`evaluation/swebench/released_checkpoints.md`](https://github.com/TIGER-AI-Lab/FIM-Midtraining/blob/main/evaluation/swebench/released_checkpoints.md).
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### 1. Serve the model with vLLM
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```bash
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CUDA_VISIBLE_DEVICES=0 \
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VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 \
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python -m vllm.entrypoints.openai.api_server \
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--model TIGER-Lab/FIM-7B \
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--served-model-name FIM-7B \
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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 65536 \
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--hf-overrides '{"max_position_embeddings": 65536}' \
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--enable-prefix-caching \
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--gpu-memory-utilization 0.9 \
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> vllm_fim7b.log 2>&1 &
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```
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Wait until the server is up (model load takes ~1 minute):
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```bash
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curl -s http://127.0.0.1:8400/v1/models
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```
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### 2. Run the agent on SWE-Bench Verified
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From an upstream, unmodified [R2E-Gym](https://github.com/R2E-Gym/R2E-Gym) checkout (Docker required):
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```bash
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export OPENAI_API_KEY=EMPTY
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export LLM_BASE_URL="http://127.0.0.1:8400/v1"
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uv run python src/r2egym/agenthub/run/edit.py runagent_multiple \
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--dataset "R2E-Gym/SWE-Bench-Verified" \
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--split "test" \
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--start_idx 0 \
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--k 500 \
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--traj_dir "./traj" \
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--exp_name "FIM-7B_swebench_verified_r1" \
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--llm_name "openai/FIM-7B" \
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--scaffold "r2egym" \
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--backend "docker" \
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--use_fn_calling False \
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--temperature 0 \
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--max_steps 40 \
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--max_steps_absolute 100 \
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--max_workers 6 \
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--max_reward_calc_time 1200 \
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--max_tokens 65536 \
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--use_existing True
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```
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For SWE-Bench Lite, use `--dataset "R2E-Gym/SWE-Bench-Lite" --k 300`.
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### 3. Score with the official SWE-bench harness
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Convert the trajectories to a submission and score with the official harness — [`evaluation/swebench/score.sh`](https://github.com/TIGER-AI-Lab/FIM-Midtraining/blob/main/evaluation/swebench/score.sh). The reported number is `resolved_instances / total_instances`.
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## Citation
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```bibtex
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@article{wang2026fim,
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title={Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models},
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author={Wang, Yubo and Liang, Jiarong and Zhang, Yuxuan and Liu, Xuye and Wei, Cong and Zhang, Yuyu and Nie, Ping and Chen, Wenhu},
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journal={arXiv preprint arXiv:2607.12463},
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year={2026}
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}
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```
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added_tokens.json
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}
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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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{%- endif %}
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{%- endfor %}
|
||||
{%- if add_generation_prompt %}
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||||
{{- '<|im_start|>assistant\n' }}
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||||
{%- endif %}
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||||
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config.json
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config.json
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{
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||||
"architectures": [
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"Qwen2ForCausalLM"
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],
|
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"attention_dropout": 0.0,
|
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"dtype": "bfloat16",
|
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"eos_token_id": 151645,
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"hidden_act": "silu",
|
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"hidden_size": 3584,
|
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"initializer_range": 0.02,
|
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"intermediate_size": 18944,
|
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"layer_types": [
|
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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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|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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|
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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",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 32768,
|
||||
"max_window_layers": 28,
|
||||
"model_type": "qwen2",
|
||||
"num_attention_heads": 28,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 4,
|
||||
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|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000.0,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": false,
|
||||
"transformers_version": "4.57.1",
|
||||
"use_cache": false,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 152064
|
||||
}
|
||||
13
generation_config.json
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generation_config.json
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{
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"do_sample": true,
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|
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|
||||
"repetition_penalty": 1.1,
|
||||
"temperature": 0.7,
|
||||
"top_k": 20,
|
||||
"top_p": 0.8,
|
||||
"transformers_version": "4.57.1"
|
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}
|
||||
151388
merges.txt
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151388
merges.txt
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Load Diff
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||||
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|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "right",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user