--- license: apache-2.0 tags: - QAnything - RAG --- A bilingual instruction-tuned model of Qwen-7B(https://huggingface.co/Qwen/Qwen-7B) for QAnything(https://github.com/netease-youdao/QAnything). 1. Run Qwen-7B-QAnything using FastChat API with Huggingface transformers runtime backend ```bash ## Step 1. Prepare the QAnything project and download local Embedding/Rerank models. git clone https://github.com/netease-youdao/QAnything.git cd /path/to/QAnything && mkdir -p tmp && cd tmp git lfs install git clone https://huggingface.co/netease-youdao/QAnything unzip QAnything/models.zip cd - && mv tmp/models . ## Step 2. Download the public LLM model (e.g., Qwen-7B-QAnything) and save to "/path/to/QAnything/assets/custom_models" cd /path/to/QAnything/assets/custom_models git clone https://huggingface.co/netease-youdao/Qwen-7B-QAnything ## Step 3. Execute the service startup command. Here we use "-b hf" to specify the Huggingface transformers backend. ## Here we use "-b hf" to specify the transformers backend that will load model in 8 bits but do bf16 inference as default for saving VRAM. cd /path/to/QAnything bash ./run.sh -c local -i 0 -b hf -m Qwen-7B-QAnything -t qwen-7b-qanything ``` 2. Run Qwen-7B-QAnything using FastChat API with vllm runtime backend ```bash ## Step 1. Prepare the QAnything project and download local Embedding/Rerank models. git clone https://github.com/netease-youdao/QAnything.git cd /path/to/QAnything && mkdir -p tmp && cd tmp git lfs install git clone https://huggingface.co/netease-youdao/QAnything unzip QAnything/models.zip cd - && mv tmp/models . ## Step 2. Download the public LLM model (e.g., Qwen-7B-QAnything) and save to "/path/to/QAnything/assets/custom_models" cd /path/to/QAnything/assets/custom_models git clone https://huggingface.co/netease-youdao/Qwen-7B-QAnything ## Step 3. Execute the service startup command. Here we use "-b vllm" to specify the Huggingface transformers backend. ## Here we use "-b vllm" to specify the vllm backend that will do bf16 inference as default. ## Note you should adjust the gpu_memory_utilization yourself according to the model size to avoid out of memory (e.g., gpu_memory_utilization=0.81 is set default for 7B. Here, gpu_memory_utilization is set to 0.85 by "-r 0.85"). cd /path/to/QAnything bash ./run.sh -c local -i 0 -b vllm -m Qwen-7B-QAnything -t qwen-7b-qanything -p 1 -r 0.85 ``` --- license: apache-2.0 License Agreement This project is open source under the Tongyi Qianwen Research License Agreement. You can view the complete license agreement in this link: [https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20RESEARCH%20LICENSE%20AGREEMENT]. During the use of this project, please ensure that your usage behavior complies with the terms and conditions of the license agreement. ---