alpaca format dataset转换格式Alpaca数据集是一个广泛使用的开源数据集,包含了大量的图像、文本和语音数据。然而,由于不同应用场景对数据格式的要求不同,有时候我们需要将Alpaca数据集的格式进行转换,以便更好地适配我们的需求。本文将介绍如何进行Alpaca数据集的格式转换,以及常用的数据格式转换工具和技巧。 一、Alpaca...
alpaca format dataset转换格式-回复 "ALPACA格式数据集转换格式"是指将数据集从一种格式转换为ALPACA格式的过程。本文将详细介绍如何逐步进行这一转换过程,以及转换为ALPACA格式的好处。 第一步是了解ALPACA格式。ALPACA是一种用于表示结构化数据的格式,其中的数据以行的形式组织,每一行称为一条记录。每条记录由多个...
Dataset and ShareGPT Format 今天学习LLM训练中常用的两种数据存储格式:sharegpt和alpaca ShareGPT ShareGPT 最早是chrome的一个插件,用于方便的分享ChatGPT的对话。2024年不再维护,API不能使用了。ShareGPT Dataset是用sharegpt插件收集的大家分享的用chatgpt生成的对话数据集。基础格式如下,需要指定role(也就是from)...
--dataset_dir: 预训练数据的目录,可包含多个以txt结尾的纯文本文件 --data_cache_dir: 指定一个存放数据缓存文件的目录 --output_dir: 模型权重输出路径 其他参数(如:per_device_train_batch_size、training_steps等)是否修改视自身情况而定。 lr=2e-4 lora_rank=8 lora_alpha=32 lora_trainable="q_proj,...
[00:00<00:00,2291.97it/s]Dataset json downloaded and prepared to /root/.cache/huggingface/datasets/json/default-8d30498d25a7aa2b/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51. Subsequent calls will reuse this data.100%|███████████████████...
This is what the Alpaca dataset can give us. Beyond that, ideally we’d like the model to be able to hold the conversation by remembering what transpired previously. For example, if you say “what did I ask you in my previous sentence”, the model should answer that you asked about the...
AlpacaDataCleaned, a project to improve the quality of the Alpaca dataset GPT-4 Alpaca Dataa project to port synthetic data creation to GPT-4 dolly-15k-instruction-alpaca-format, an Alpaca-compatible version ofDatabricks' Dolly 15k human-generated instruct dataset(seeblog) ...
If you have your own instruction tuning dataset, editDATA_PATHinfinetune.pyto point to your own dataset. Make sure it has the same format asalpaca_data_cleaned.json. Run the fine-tuning script: cog run python finetune.py This takes 3.5 hours on a 40GB A100 GPU, and more than that fo...
reference_outputs: The outputs of the reference model. Same format as model_outputs. By default, this is text-davinci003 outputs on AlpacaEval dataset. output_path: Path for saving annotations and leaderboard.If you don't have the model outputs, you can use evaluate_from_model and pass a ...
If you have your own instruction tuning dataset, edit DATA_PATH in finetune.py to point to your own dataset. Make sure it has the same format as alpaca_data_cleaned.json. Run the fine-tuning script: cog run python finetune.py This takes 3.5 hours on a 40GB A100 GPU, and more than...