初始化项目，由ModelHub XC社区提供模型

Model: OpenDevin/CodeQwen1.5-7B-OpenDevin
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- en
+pipeline_tag: text-generation
+---
+# CodeQwen1.5-7B-OpenDevin
+
+## Introduction
+CodeQwen1.5-7B-OpenDevin is a code-specific model targeting on OpenDevin Agent tasks. 
+The model is finetuned from CodeQwen1.5-7B, the code-specific large language model based on Qwen1.5 pretrained on large-scale code data.
+CodeQwen1.5-7B is strongly capable of understanding and generating codes, and it supports the context length of 65,536 tokens (for more information about CodeQwen1.5, please refer to the [blog post](https://qwenlm.github.io/blog/codeqwen1.5/) and [GitHub repo](https://github.com/QwenLM/Qwen1.5)). 
+The finetuned model, CodeQwen1.5-7B-OpenDevin, shares similar features, while it is designed for rapid development, debugging, and iteration.
+
+## Performance
+We evaluate CodeQwen1.5-7B-OpenDevin on SWE-Bench-Lite by implementing the model on OpenDevin CodeAct 1.3 and follow the OpenDevin evaluation pipeline. 
+CodeQwen1.5-7B-OpenDevin successfully solves 4 problems by commmiting pull requests targeting on the issues. 
+
+## Requirements
+The code of Qwen1.5 has been in the latest Hugging face transformers and we advise you to install `transformers>=4.37.0`, or you might encounter the following error:
+```
+KeyError: 'qwen2'.
+```
+
+## Quickstart
+
+To use local models to run OpenDevin, we advise you to deploy CodeQwen1.5-7B-OpenDevin on a GPU device and access it through OpenAI API
+
+```bash
+python -m vllm.entrypoints.openai.api_server --model OpenDevin/CodeQwen1.5-7B-OpenDevin --dtype auto --api-key token-abc123
+```
+
+For more details, please refer to the official documentation of [vLLM for OpenAI Compatible server](https://docs.vllm.ai/en/stable/serving/openai_compatible_server.html). 
+
+After the deployment, following the guidance of [OpenDevin](https://github.com/OpenDevin/OpenDevin) and run the following command to set up environment variables:
+
+```bash
+# The directory you want OpenDevin to work with. MUST be an absolute path!
+export WORKSPACE_BASE=$(pwd)/workspace;
+export LLM_API_KEY=token-abc123;
+export LLM_MODEL=OpenDevin/CodeQwen1.5-7B-OpenDevin;
+export LLM_BASE_URL=http://localhost:8000/v1;
+```
+
+and run the docker command:
+
+```bash
+docker run \
+    -it \
+    --pull=always \
+    -e SANDBOX_USER_ID=$(id -u) \
+    -e LLM_BASE_URL=$LLM_BASE_URL \
+    -e LLM_API_KEY=$LLM_API_KEY \
+    -e LLM_MODEL=$LLM_MODEL \
+    -e WORKSPACE_MOUNT_PATH=$WORKSPACE_BASE \
+    -v $WORKSPACE_BASE:/opt/workspace_base \
+    -v /var/run/docker.sock:/var/run/docker.sock \
+    -p 3000:3000 \
+    --add-host host.docker.internal:host-gateway \
+    ghcr.io/opendevin/opendevin:0.5
+```
+
+Now you should be able to connect `http://localhost:3000/`. Set up the configuration at the frontend by clicking the button at the bottom right, and input the right model name and api key. 
+Then, you can enjoy playing with OpenDevin based on CodeQwen1.5-7B-OpenDevin!
+
+## Note
+This is just a finetuning experiment, and we admit that the performance of the model is still lagging far behind GPT-4. In the future, we will update our datasets for agent-specific finetuning and provide better and larger models. Stay tuned!
+
+## Citation
+
+```
+@misc{codeqwen1.5,
+    title = {Code with CodeQwen1.5},
+    url = {https://qwenlm.github.io/blog/codeqwen1.5/},
+    author = {Qwen Team},
+    month = {April},
+    year = {2024}
+}
+```

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 2,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 13440,
+  "max_position_embeddings": 65536,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 4,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000,
+  "rotary_emb_base": 1000000,
+  "seq_length": 65536,
+  "sliding_window": 65536,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.39.3",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 92416
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

generation_config.json

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+{
+  "bos_token_id": 2,
+  "do_sample": true,
+  "eos_token_id": [
+    4,
+    2
+  ],
+  "pad_token_id": 92298,
+  "repetition_penalty": 1.0,
+  "temperature": 1.0,
+  "top_p": 0.95,
+  "transformers_version": "4.39.3"
+}

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tokenizer_config.json

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+  "add_eos_token": false,
+  "add_prefix_space": false,
+  "additional_special_tokens": ["<|im_start|>", "<|im_end|>", "<fim_prefix>", "<fim_middle>", "<fim_suffix>", "<fim_pad>"],
+  "bos_token": "<|endoftext|>",
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+  "eos_token": "<|im_end|>",
+  "legacy": false,
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+  "pad_token": "<fim_pad>",
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+  "tokenizer_class": "PreTrainedTokenizerFast",
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+  "add_prefix_space": true,
+  "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}"
+}