Cmd Shell For Download Files

本文介绍了一个使用VBS脚本进行文件下载的例子。通过创建Microsoft.XMLHTTP对象发送GET请求并利用ADODB.Stream对象保存响应内容到本地。此过程展示了如何实现自动化的文件下载任务。

Set xPost = createObject("Microsoft.XMLHTTP")
xPost.Open "GET","http://yoursite:8080/SharePoint/NewsTar/Antivirus/unlocker1.8.5.exe",0 '下载文件的地址
xPost.Send()
Set sGet = createObject("ADODB.Stream")
sGet.Mode = 3
sGet.Type = 1
sGet.Open()
sGet.Write(xPost.responseBody)
sGet.SaveToFile "./unlocker1.8.5.exe",2 '保存文件的路径和文件名

保存为.vbs 执行下载

conda conda is a language-agnostic package manager. Install Transformers from the conda-forge channel in your newly created virtual environment. conda install conda-forge::transformers Set up After installation, you can configure the Transformers cache location or set up the library for offline usage. Cache directory When you load a pretrained model with from_pretrained(), the model is downloaded from the Hub and locally cached. Every time you load a model, it checks whether the cached model is up-to-date. If it’s the same, then the local model is loaded. If it’s not the same, the newer model is downloaded and cached. The default directory given by the shell environment variable HF_HUB_CACHE is ~/.cache/huggingface/hub. On Windows, the default directory is C:\Users\username\.cache\huggingface\hub. Cache a model in a different directory by changing the path in the following shell environment variables (listed by priority). HF_HUB_CACHE (default) HF_HOME XDG_CACHE_HOME + /huggingface (only if HF_HOME is not set) Offline mode To use Transformers in an offline or firewalled environment requires the downloaded and cached files ahead of time. Download a model repository from the Hub with the snapshot_download method. Refer to the Download files from the Hub guide for more options for downloading files from the Hub. You can download files from specific revisions, download from the CLI, and even filter which files to download from a repository. from huggingface_hub import snapshot_download snapshot_download(repo_id="meta-llama/Llama-2-7b-hf", repo_type="model") Set the environment variable HF_HUB_OFFLINE=1 to prevent HTTP calls to the Hub when loading a model. HF_HUB_OFFLINE=1 \ python examples/pytorch/language-modeling/run_clm.py --model_name_or_path meta-llama/Llama-2-7b-hf --dataset_name wikitext ... Another option for only loading cached files is to set local_files_only=True in from_pretrained(). from transformers import LlamaForCausalLM model = LlamaForCausalLM.from_pretrained("./path/to/local/directory", local_files_only=True) Update on GitHub 详细解释一下
最新发布
12-11
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