参考【GitHub - AIAnytime/Code-Llama-QA-Bot】,基于llama.cpp进行部署。 llama2-code cpu运行测试地址,llama.cpp版本的模型地址【CodeLlama-7B-Instruct-GGUF】。 3.4 vscode插件 看到code-llama,就想能不能用到vscode,方便开发。具体参考【https://github.com/xNul/code-llama-for-vscode】 第一步参考codel...
对于Python 微调,论文将初始学习率设置为 1e−4。对于 Code Llama - Instruct,他们用一个批次大小为 524,288 个 token 进行训练,总共训练了大约 50 亿个 token。 Long Context finetuning 对于长上下文微调 (LCFT),作者使用了2e−5的学习率 16384的序列长度,并重置 RoPE 频率,基值为θ = 10^6 ...
通过长序列微调(long context fine-tuning),CodeLLaMA系列模型支持高达10万个tokens的输入文本,明显优于只支持4K的Llama 2。在非常长的代码文件中仍表现稳定。 在Python代码生成基准测试数据集如HumanEval和MBPP上取得最先进的成绩,尤其是与开源模型相比,基本是最强的。同时也在多语言数据集MultiPL-E上表现强劲。 Code...
由于CodeLlama-70B-Instruct是开源的预训练模型,相比较榜单其它模型,其优势非常明显。其他模型大多数是微调或者闭源模型。 根据官网的论文介绍,CodeLLaMA的特点如下: 通过长序列微调(long context fine-tuning),CodeLLaMA系列模型支持高达10万个tokens的输入文本,明显优于只支持4K的Llama 2。在非常长的代码文件中仍表现...
This repository is adapted from https://github.com/pacman100/LLM-Workshop, which supports fine-tuning a number of models, including Code Llama. However, a number of problems were encountered when using the original repository with Code Llama. This repository contains improvements like context-level...
Code Llama 2 fine-tuning supports a number of hyperparameters, each of which can impact the memory requirement, training speed, and performance of the fine-tuned model: epoch –The number of passes that the fine-tuning algorithm takes through the training dataset. Must be an integer greater th...
Our fork patches support for Code Llama and an open issue causing CUDA OOMs while saving LORA state dicts for 70B models. Best of all, using Modal for fine-tuning means you never have to worry about infrastructure headaches like building images and provisioning GPUs. If a training script runs...
Code Llama – Instruct is an instruction fine-tuned and aligned variation of Code Llama. Instruction tuning continues the training process, but with a different objective. The model is fed a natural language instruction input and the expected output. This makes it better at understanding what peopl...
置顶Llama 2详解 CodeLearner 华中科技大学 电子信息硕士 0 前言 LLM(Large Language Model)应该是今年深度学习领域一项具有革命性的技术突破,如果你尝试使用过OpenAI的ChatGPT3.5那么你一定会惊叹AI的强大。而对于这样具有&…阅读全文 赞同924 54 条评论 分享收藏 ...
While many contemporary large language models (LLMs) can process lengthy input, they still struggle to fully utilize information within the long context, known as the lost-in-the-middle challenge. 2 Paper Code Efficient multi-prompt evaluation of LLMs microsoft/promptbench • • 27 May 2024...