初始化项目，由ModelHub XC社区提供模型

Model: TIGER-Lab/FIM-Mid-7B
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+base_model:
+- Qwen/Qwen2.5-Coder-7B-Instruct
+datasets:
+- TIGER-Lab/FIM-Midtraining-400K
+tags:
+- code
+- software-engineering
+- fim
+---
+
+# FIM-Mid-7B
+
+[📄 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)
+
+**FIM-Mid-7B** is the mid-trained checkpoint of the FIM 7B pipeline: `Qwen2.5-Coder-7B-Instruct` after function-aware FIM mid-training, **before** agent post-training. Post-training this checkpoint on R2E-Gym agent trajectories produces [TIGER-Lab/FIM-7B](https://huggingface.co/TIGER-Lab/FIM-7B).
+
+It is released for reproducibility and further post-training. The paper deliberately never scores mid-training-only checkpoints — a FIM-only model has degraded instruction-following and cannot be compared fairly against instruction-tuned baselines; every reported gain is one that *survives* post-training.
+
+## Training
+
+- **Base model**: [`Qwen/Qwen2.5-Coder-7B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct)
+- **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) — AdamW, lr `1.0e-5`, cosine schedule, warmup ratio `0.1`, weight decay `0.05`, one epoch, sequence length `32768`, bf16 (as-run copy: [`FIM_Midtrain_7B.yaml`](https://github.com/TIGER-AI-Lab/FIM-Midtraining/blob/main/midtraining/configs/FIM_Midtrain_7B.yaml))
+- **Post-training**: none — see [TIGER-Lab/FIM-7B](https://huggingface.co/TIGER-Lab/FIM-7B) for the post-trained agent model
+
+## Serve with vLLM
+
+A standard Qwen2.5 checkpoint; no overrides needed at its native 32768 context:
+
+```bash
+CUDA_VISIBLE_DEVICES=0 \
+python -m vllm.entrypoints.openai.api_server \
+  --model TIGER-Lab/FIM-Mid-7B \
+  --served-model-name FIM-Mid-7B \
+  --host 127.0.0.1 \
+  --port 8400 \
+  --tensor-parallel-size 1 \
+  --max-model-len 32768 \
+  --gpu-memory-utilization 0.9 \
+  > vllm_fim_mid7b.log 2>&1 &
+```
+
+## Post-training
+
+To reproduce FIM-7B, run R2E-Gym trajectory SFT from this checkpoint — the exact config is [`posttraining/r2egym/FIM_Posttrain_7B.yaml`](https://github.com/TIGER-AI-Lab/FIM-Midtraining/blob/main/posttraining/r2egym/FIM_Posttrain_7B.yaml) (LLaMA-Factory, full fine-tuning, lr `1.0e-5`, 2 epochs, cutoff 32768), which already points at this repo id. See [`posttraining/r2egym/`](https://github.com/TIGER-AI-Lab/FIM-Midtraining/tree/main/posttraining/r2egym) for the walkthrough.
+
+## Citation
+
+```bibtex
+@article{wang2026fim,
+  title={Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models},
+  author={Wang, Yubo and Liang, Jiarong and Zhang, Yuxuan and Liu, Xuye and Wei, Cong and Zhang, Yuyu and Nie, Ping and Chen, Wenhu},
+  journal={arXiv preprint arXiv:2607.12463},
+  year={2026}
+}
+```

added_tokens.json

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+  "<|vision_end|>": 151653,
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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\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>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\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" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "dtype": "bfloat16",
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+  "hidden_act": "silu",
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+    "full_attention",
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+  "max_window_layers": 28,
+  "model_type": "qwen2",
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+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.6",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

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tokenizer_config.json

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