## CPU Details Details that do not depend upon whether you are running on CPU for Linux, Windows, or macOS. ### LLaMa.cpp Default llama.cpp model is LLaMa2 GPTQ model from TheBloke: * Run LLaMa.cpp LLaMa2 model: With documents in `user_path` folder, run: ```bash # if don't have wget, download to repo folder using below link wget https://huggingface.co/TheBloke/Llama-2-7b-Chat-GGUF/resolve/main/llama-2-7b-chat.Q6_K.gguf python generate.py --base_model='llama' --prompt_type=llama2 --score_model=None --langchain_mode='UserData' --user_path=user_path ``` For another llama.cpp model: * Choose from [TheBloke](https://huggingface.co/TheBloke), then with documents in `user_path` folder, run: ```bash python generate.py --base_model=llama --model_path_llama=https://huggingface.co/TheBloke/Llama-2-7b-Chat-GGUF/resolve/main/llama-2-7b-chat.Q6_K.gguf --score_model=None --langchain_mode='UserData' --user_path=user_path ``` For `llama.cpp` based models on CPU, for computers with low system RAM or slow CPUs, we recommend running: ```bash python generate.py --base_model=llama --model_path_llama=https://huggingface.co/TheBloke/Llama-2-7b-Chat-GGUF/resolve/main/llama-2-7b-chat.Q6_K.gguf --llamacpp_dict="{'use_mlock':False,'n_batch':256}" --max_seq_len=512 --score_model=None --langchain_mode='UserData' --user_path=user_path ``` ### GPT4ALL * Choose Model from GPT4All Model explorer [GPT4All-J compatible model](https://gpt4all.io/index.html). One does not need to download manually, the GPT4ALL package will download at runtime and put it into `.cache` like Hugging Face would. * With documents in `user_path` folder, run: ```bash python generate.py --base_model=gptj --model_path_gptj=ggml-gpt4all-j-v1.3-groovy.bin --score_model=None --langchain_mode='UserData' --user_path=user_path ``` or ```bash python generate.py --base_model=gpt4all_llama --model_name_gpt4all_llama=ggml-wizardLM-7B.q4_2.bin --score_model=None --langchain_mode='UserData' --user_path=user_path ``` However, `gpjt` model often gives [no output](FAQ.md#gpt4all-not-producing-output), even outside h2oGPT. See [GPT4All](https://github.com/nomic-ai/gpt4all) for details on installation instructions if you encounter any issues. ### Low-memory For more information about low-memory recommendations, see [Low Memory](FAQ.md#low-memory-mode).