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git clone https://github.com/FlagAlpha/Llama2-Chinese.gitcdLlama2-Chinese docker build -f docker/Dockerfile -t flagalpha/llama2-chinese-7b:gradio. 第二步:通过docker-compose启动chat_gradio cdLlama2-Chinese/docker doker-compose up -d --build ...
git clone https://github.com/ggerganov/llama.cpp.git !(cd llama.cpp; make) # make LLAMA_CUBLAS=1 if GPU !wget https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/resolve/main/llama-2-13b-chat.ggmlv3.q4_0.bin !llama.cpp/main ... - llama-2-13b-chat.ggmlv3.q4_0.bin (...
Colossal-AI 开源地址:https://github.com/hpcaitech/ColossalAI 参考链接:https://www.hpc-ai.tech/blog/one-half-day-of-training-using-a-few-hundred-dollars-yields-similar-results-to-mainstream-large-models-open-source-and-commercial-free-domain-specific-LLM-solution...
git clone git@github.com:AmineDiro/cria.gitcdcria/docker The api will load the model located in/app/model.binby default. You should change the docker-compose file with ggml model path for docker to bind mount. You can also change environement variables for your specific config. Alternatively...
git clone https://github.com/tairov/llama2.mojo.git Then, open the repository folder: cdllama2.mojo Now, let's download the model and the tokenizer wget https://huggingface.co/kirp/TinyLlama-1.1B-Chat-v0.2-bin/resolve/main/tok_tl-chat.bin wget https://huggingface.co/kirp/TinyLlama-1.1...
git clone https://github.com/FlagAlpha/Llama2-Chinese.git cd Llama2-Chinese docker build -f docker/Dockerfile -t flagalpha/llama2-chinese-7b:gradio . 第二步:通过docker-compose启动chat_gradio cd Llama2-Chinese/docker doker-compose up -d --build 🤖 模型预训练 虽然Llama2的预训练数据相对于...
git clone https://github.com/FlagAlpha/Llama2-Chinese.gitcdLlama2-Chinese docker build -f docker/Dockerfile -t flagalpha/llama2-chinese-7b:gradio. 第二步:通过docker-compose启动chat_gradio cdLlama2-Chinese/docker doker-compose up -d --build ...
仅仅两周时间，该项目在 Hugging Face 上收获过万次下载，并在 GitHub 上获得了 1200 Stars。据项目介绍，Chinese-Llama-2-7b 开源的内容包括完全可商用的中文版 Llama2 模型及中英文 SFT 数据集，输入格式严格遵循 llama-2-chat 格式，兼容适配所有针对原版 llama-2-chat 模型的优化。项目地址：https://github...
llama.cpp中使用AWQ:https://github.com/ggerganov/llama.cpp/tree/master/awq-py 以下是LoRA模型(含emb/lm-head),与上述完整模型一一对应。需要注意的是LoRA模型无法直接使用,必须按照教程与重构模型进行合并。推荐网络带宽不足,手头有原版Llama-2且需要轻量下载的用户。