openbuddy-llama3.2-3b-v23.2-131k-Q4_K_M-GGUF:Llama3.2基础多语言文本生成GGUF模型

基于Llama3.2的多语言文本生成模型,支持中、英、法等多语言,已转换为GGUF格式,适用于llama.cpp,可通过CLI或服务器模式运行。【此简介由AI生成】

分支1Tags0

base_model: OpenBuddy/openbuddy-llama3.2-3b-v23.2-131k language:

  • zh
  • en
  • fr
  • de
  • ja
  • ko
  • it
  • fi license: llama3.2 pipeline_tag: text-generation tags:
  • llama-3.2
  • llama-cpp
  • gguf-my-repo

ff670/openbuddy-llama3.2-3b-v23.2-131k-Q4_K_M-GGUF

This model was converted to GGUF format from OpenBuddy/openbuddy-llama3.2-3b-v23.2-131k using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo ff670/openbuddy-llama3.2-3b-v23.2-131k-Q4_K_M-GGUF --hf-file openbuddy-llama3.2-3b-v23.2-131k-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo ff670/openbuddy-llama3.2-3b-v23.2-131k-Q4_K_M-GGUF --hf-file openbuddy-llama3.2-3b-v23.2-131k-q4_k_m.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo ff670/openbuddy-llama3.2-3b-v23.2-131k-Q4_K_M-GGUF --hf-file openbuddy-llama3.2-3b-v23.2-131k-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo ff670/openbuddy-llama3.2-3b-v23.2-131k-Q4_K_M-GGUF --hf-file openbuddy-llama3.2-3b-v23.2-131k-q4_k_m.gguf -c 2048

项目介绍

基于Llama3.2的多语言文本生成模型,支持中、英、法等多语言,已转换为GGUF格式,适用于llama.cpp,可通过CLI或服务器模式运行。【此简介由AI生成】

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