bug:huggingface-cli: error: argument {env,login,whoami,logout,repo,lfs-enable-largefiles,lfs-multipart-upload,scan-cache,delete-cache}: invalid choice: 'download' (choose from 'env', 'login', 'whoami', 'logout', 'repo', 'lfs-enable-largefiles', 'lfs-multipart-upload', 'scan-cache',...
acache_dirwhich you can specify if you want to control where on disk the files are cached. Check out the source code for all possible params (we'll create a real doc page in the future). Bonus:snapshot_download snapshot_download()downloads all the files from the remote repository at th...
>>> huggingface-cli download --help usage: huggingface-cli download REPO_ID [PATH] [--help] [--repo-type REPO_TYPE] [--revision REVISION] [--token TOKEN] [--allow-patterns ALLEW_PATTERNS] [--ignore-patterns IGNORE_PATTERNS] [--to-local-dir] [--local-dir-use-symlinks] ...
So far all of the pretrained weights available here are pretrained on ImageNet with a select few that have some additional pretraining (see extra note below). ImageNet was released for non-commercial research purposes only (https://image-net.org/download). It's not clear what the implication...
files = [file[0]forfileindata_ls] data = pd.DataFrame(data_ls,columns = ['文件名','大小'])returndata, files# 模型下载到当前目录下的"./download"目录defdownload_file(repo_id,filenames):print(filenames) repo_name = repo_id.replace("/","---")forfilenameinfilenames:print(filename...
The huggingface_hub library provides a simple way to do all these things with Python. Key features Download files from the Hub. Upload files to the Hub. Manage your repositories. Run Inference on deployed models. Search for models, datasets and Spaces. Share Model Cards to document your ...
force_download=False, ) # 对文本 sents = [ '选择珠江花园的原因就是方便。', '笔记本的键盘确实爽。', '房间太小。其他的都一般。', '今天才知道这书还有第6卷,真有点郁闷.', '机器背面似乎被撕了张什么标签,残胶还在。', ] # 对文本编码encode, out就是每个字符的id number ...
将hugging face的权重下载到本地，然后我们之后称下载到本地的路径为llama_7b_localpath 【
Hosted inference API for all models publicly available. In-browser widgets to play with the uploaded models. Anyone can upload a new model for your library, they just need to add the corresponding tag for the model to be discoverable. Fast downloads! We use Cloudfront (a CDN) to geo-repli...
Before you begin, make sure you have all the necessary libraries installed : pip install --upgrade --upgrade-strategy eager optimum[habana] - from transformers import Trainer, TrainingArguments+ from optimum.habana import GaudiTrainer, GaudiTrainingArguments# Download a pretrained model from the Hub ...