此外,Code Llama 的「Unnatural」34B 版本在 HumanEval 数据集上的 pass@1 接近了 GPT-4(62.2% vs 67.0%)。 在本文,我们将紧跟趋势介绍如何在本地CPU推理上运行量化版本的开源CodeLlama 7B Python - GGUF。 量化快速入门 我们首先简单介绍一下量化的概念: 量化是一种减少用于表示数字或值的比特数的技术。
code llama就是在llama2模型【一文看懂llama2(原理,模型,训练)】的基础上,利用代码数据进行训练和微调,提高llama2在代码生成上的能力。 code llama提供了三种模型,每种模型包含7B,13B,34B三个尺寸,支持多种编程语言,如Python,C++, Java,PHP, Typescript (Javascript),C#,Bash等。 Code Llama,代码生成的基础模型;...
2.1 Nous Hermes Llama 2 7B Chat (GGML q4_0) 2.2 Nous Hermes Llama 2 13B Chat (GGML q4_0) 2.3 Nous Hermes Llama 2 70B Chat (GGML q4_0) 2.4 Code Llama 7B Chat (GGUF Q4_K_M) 2.5 Code Llama 13B Chat (GGUF Q4_K_M) 2.6 Phind Code Llama 34B Chat (GGUF Q4_K_M)...
Phind Code Llama 34B Chat (GGUF Q4_K_M) 34B 20.22GB 22.72GB 1.1 安装LlamaGPT 在 umbrelOS Running LlamaGPT on an umbrelOS home server is one click. Simply install it from the Umbrel App Store. 1.2 安装LlamaGPT on M1/M2 Mac Make sure your have Docker and Xcode installed. Then...
You can either manually download the GGUF file or directly use any llama.cpp-compatible models from Hugging Face by using this CLI argument: -hf <user>/<model>[:quant] After downloading a model, use the CLI tools to run it locally - see below. llama.cpp requires the model to be store...
# run the inference./main -m ./models/7B/ggml-model-q4_0.gguf -n 128 此步可以省略,直接下载别人转换好的量化模型即可。https://huggingface.co/TheBloke/Llama-2-7b-Chat-GGUF 运行 命令行交互模式 ./main -m ./models/llama-2-7b.Q4_0.gguf -i -n 256 --color ...
Phind Code Llama 34B Chat (GGUF Q4_K_M) DeviceGeneration speed M1 Max MacBook Pro (64GB RAM) 10.26 tokens/sec Roadmap and contributing We're looking to add more features to LlamaGPT. You can see the roadmap here. The highest priorities are: Moving the model out of the Docker image ...
2.5 Code Llama 13B Chat (GGUF Q4_K_M) Device Generation speed M1 Max MacBook Pro (64GB RAM) 25 tokens/sec 2.6 Phind Code Llama 34B Chat (GGUF Q4_K_M) Device Generation speed M1 Max MacBook Pro (64GB RAM) 10.26 tokens/sec
CodeLlama-34b官网版本:https://pan.baidu.com/s/1vEw0pFgIkctPUN4_5_6pIQ?pwd=q8eu 3 安装并运行 llama2.c llama2.c 是开源项目,支持在纯C语言下训练并运行 Llama 2模型 3.1 下载并构建llama.cpp git clone https://github.com/karpathy/llama2.c cd llama2.c make run 3.2 转换model到llama...
services: llamacpp-server: image: ghcr.io/ggml-org/llama.cpp:server ports: - 8080:8080 volumes: - ./models:/models environment: # alternatively, you can use "LLAMA_ARG_MODEL_URL" to download the model LLAMA_ARG_MODEL: /models/my_model.gguf LLAMA_ARG_CTX_SIZE: 4096 LLAMA_ARG_N_...