注册 Hugging Face 后的官网创建模型的教程_huggingface如何创建

Welcome

Create a new model

From the website

Hub documentation

Take a first look at the Hub features

Programmatic access

Use the Hub’s Python client library

Getting started with our git and git-lfs interface

You can create a repository from the CLI (skip if you created a repo from the website)

pip install huggingface_hub
						

You already have it if you installed transformers or datasets
	
						

huggingface-cli login
						

Log in using a token from huggingface.co/settings/tokens
						

Create a model or dataset repo from the CLI if needed
						

huggingface-cli repo create repo_name --type {model, dataset, space}
					

Clone your model, dataset or Space locally

Make sure you have git-lfs installed
					

(https://git-lfs.github.com)
					

git lfs install
					

git clone https://huggingface.co/username/repo_name
				

Then add, commit and push any file you want, including larges files

 save files via `.save_pretrained()` or move them here
						

git add .
						

git commit -m "commit from $USER"
						

git push
					

In most cases, if you're using one of the compatible libraries, your repo will then be accessible from code, through its identifier: username/repo_name

For example for a transformers model, anyone can load it with:

					tokenizer = AutoTokenizer.from_pretrained("username/repo_name")
					model = AutoModel.from_pretrained("username/repo_name")