为了帮助你使用huggingface_hub库中的snapshot_download函数下载所需的模型快照,并处理下载后的文件,我将按照你的提示分点进行回答,并包含相关的代码片段。 1. 确认huggingface_hub库已安装 首先,确保你已经安装了huggingface_hub库。如果尚未安装,可以使用以下命令进行安装: bash pip install huggingface_hub 2. 导入...
from huggingface_hub import snapshot_download #自行选择模型,自行修改下面参数(第一步的相对地址) model_addr = 'Qwen/Qwen1.5-1.8B-Chat' #提取模型库名和模型名称 model_repo = model_addr.split('/')[0] model_name = model_addr.split('/')[1] # 下载模型 snapshot_download( repo_id=f"{model...
fromhuggingface_hubimportsnapshot_download# 下载模型snapshot_download(repo_id='THUDM/chatglm2-6b',repo_type="model",# 可选 [dataset,model]local_dir='/home/dev/datasets/glm',# 下载到本地的路径resume_download=True,# 断点续传)# 下载数据snapshot_download(repo_id='BAAI/COIG-PC',repo_type="...
A completely different solution would be to provide a context manager that downloads a repo to a random temporary location, people do whatever they need to do and then the context manager removes the downloaded snapshot. This would address this use case, but I feel it's out of scope of w...
Bonus:snapshot_download snapshot_download()downloads all the files from the remote repository at the specified revision, stores it to disk (in a versioning-aware way) and returns its local file path. Parameters: arepo_idin the formatnamespace/repository ...
@@ -18,6 +18,7 @@ def snapshot_download( library_name: Optional[str] = None, library_version: Optional[str] = None, user_agent: Union[Dict, str, None] = None, use_auth_token: Union[bool, str, None] = None, ) -> str: """ Downloads a whole snapshot of a repo's files ...
构造附件 att = MIMEText(open(Filename, "rb").read(), "base64", "utf-8") att["Content-...
import{snapshotDownload}from"@huggingface/hub";constdirectory=awaitsnapshotDownload({repo:'foo/bar',});console.log(directory); The code use internally thedownloadFileToCacheDirfunction. Note: this does not work in the browser When uploading large files, you may want to run thecommitcalls inside...
from huggingface_hub import snapshot_download snapshot_download("stabilityai/stable-diffusion-2-1") Files will be downloaded in a local cache folder. More details in this guide. Login The Hugging Face Hub uses tokens to authenticate applications (see docs). To log in your machine, run the ...
步骤1:在./ChatGLM-6B/下创建文件夹./ChatGLM-6B/chatglm-6b/用于存放本地模型 mkdir chatglm-6b 步骤2:进入chatglm-6b环境,并进入python终端 conda activate chatglm-6b python 步骤3:调用huggingface_hub下载ChatGLM-6B模型到指定本地路径 from huggingface_hub import snapshot_download ...