Each option can be implemented separately in a different PR. CLI implementation can be found in./commands/delete_cache.pywhile the cache scan tool itself is in./utils/_cache_manager.py We are interested in cleaning cached models which were not accessed in the past N days. Would it make se...
--local-dir-use-symlinks False表示不在默认路径~/.cache/huggingface/hub中保存模型,如果设为true,则保存在默认路径,指定目录只是超链接。 bug:huggingface-cli: error: argument {env,login,whoami,logout,repo,lfs-enable-largefiles,lfs-multipart-upload,scan-cache,delete-cache}: invalid choice: 'download'...
$ huggingface-cli upload --repo-type [repo_type] [repo_id] [path/to/local_file_or_directory] [path/to/repo_file_or_directory] Scan cache to see downloaded repositories and their disk usage $ huggingface-cli scan-cache Delete the cache interactively $ huggingface-cli delete-cache...
pipeline:218 - Note: HuggingFace caches the downloaded models in ~/.cache/huggingface/ (or C:\Users\<username>\.cache\huggingface\ on Windows). If you have already downloaded the model before, the download should be much faster. If you run out of disk space, you can delete the cache ...
huggingface-cli login 登录成功后,可以使用create_repo()函数创建新的repo。 from huggingface_hub import create_repo repo_url = create_repo(name="github-issues", repo_type="dataset") repo_url 'https://huggingface.co/datasets/lewtun/github-issues' ...
transformers-cli s3 ls You can also delete unneeded files: transformers-cli s3 rm … Quick tour of pipelines New in versionv2.3:Pipelineare high-level objects which automatically handle tokenization, running your data through a transformers model and outputting the result in a structured object. ...
usage: huggingface-cli [<args>] huggingface-cli: error: invalid choice: 'download' (choose from 'env', 'login', 'whoami', 'logout', 'repo', 'lfs-enable-largefiles', 'lfs-multipart-upload', 'scan-cache', 'delete-cache') Contributor...
EDIT (before reading below): motivation is the same but the plan has been slightly improved (see this comment). Basically, the plan is: add delete_patterns in upload_folder implement commit_in_chunks to chained commits in a PR implement ...
这种方式,huggingface 会从 huggingface hub上下载模型,缓存到本地的~/.cache/huggingface/transformers目录。如果想修改缓存的目录,可以设置 HF_HOME环境变量。 fromtransformersimportBertModelmodel=BertModel.from_pretrained("bert-base-cased") 2.3 保存模型 ...