以下是Llama2用telegram群聊数据进行丐版微调的教程,只需要花上十几块人民币再加上一个小时,就可以得到一个你想要的Llama 2了。以下是Llama2在微调后的工作效果: 在Telegram 中模拟对话 目标很明确,就是对Llama 2进行微调,这样可以自动生成我与朋友进行多年的群聊中发生的对话。第一步是从 Telegram 导出数据,这...
好久没做 weekend project 了,那么,让我们来 fine-tune 自己的 LLaMA-2 吧!按照下面的步骤,我们甚至不需要写一行代码,就可以完成 fine-tunning! 第一步:准备训练脚本 很多人不知道的是,LLaMA-2 开源后,Meta 同步开源了llama-recipes这个项目,帮助对 fine-tune LLaMA-2 感兴趣的小伙伴更好地 “烹饪” 这个模型。
To solve this problem, Matt Shumer, founder and CEO of OthersideAI, has created claude-llm-trainer, a tool that helps you fine-tune Llama-2 for a specific task with a single instruction. How to use claude-llm-trainer Claude-llm-traineris a Google Colab notebook that contains the code fo...
首先，访问 llama-recipes 项目，此项目为对 LLaMA-2 进行 fine-tuning 的新手提供了极大便利。下载并准备训练数据集 GuanacoDataset，特别推荐选择适用于指令遵循任务的 guanaco_non_chat-utf8.json，但根据实际情况，guanaco_non_chat_mini_52K-utf8.json 也是一个高效选项。将数据集重命名为 alpaca_...
笔记修改自博主@AI探索与发现 参考视频:https://www.youtube.com/watch?v=LPmI-Ok5fUcllama3微调训练finetune中文写作模型,Lora小说训练,利用AI写小说llama3-novel中文网络小说写作模型 https://pan.quark.cn/s/dcd9799885c4llama3-novel中文绅士小说写作模型 https://pan.
历时四五天,终于上手llama2 finetune recipe 修了无数的repo里面的bug 也被机器里面nvidia驱动坑了不少[打call] 从入门到稍微精通[赢牛奶]
tune Llama 2 models using customers’ own data to achieve better performance for downstream tasks. However, due to Llama 2 model’s large number of parameters, full fine-tuning could be prohibitively expensive and time consuming. Parameter-Efficient Fine-Tuning (PEFT) ...
In addition, you can fine-tune Llama2 7B, 13B, and 70B pre-trained text generation models via SageMaker JumpStart. Fine-tune Llama2 models You can fine-tune the models using either the SageMaker Studio UI or SageMaker Python SDK. We discuss both methods in this section. No-code...
In a single-server configuration with a single GPU card, the time taken to fine-tune Llama 2 7B ranges from 5.35 hours with one Intel® Data Center GPU Max 1100 to 2.4 hours with one Intel® Data Center GPU Max 1550. When the configuration is scaled up to 8 GPUs, th...
So if you, e.g., usemeta-llama/Llama-2-7b-hfas your base model, then be aware that the default of that isuse_cache=True(comparethe config on HuggingFace)! And so will be the default for your finetuned version, unless you specify something else. ...