初始化项目，由ModelHub XC社区提供模型

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

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}
+}
+```