Example to download the model https://huggingface.co/xai-org/grok-1 (script code from the same repo) using HuggingFace CLI: git clone https://github.com/xai-org/grok-1.git && cd grok-1 pip install huggingface_hub[hf_transfer] huggingface-cli download xai-org/grok-1 --repo-type model ...
What you have saved is the model which the trainer was going to tune and you should be aware that predicting, training, evaluation and etc, are the utilities of transformers.trainer.Trainer object, not transformers.models.xlm_roberta.modeling_xlm_roberta.XLMRobertaForQuestionAnswering. Based on...
https://huggingface.co/models 例如,我想下載“bert‑base‑uncased”,但找不到“下載”鏈接。請幫忙。還是不能下載? 參考解法 方法1: Accepted answer is good, but writing code to download model is not always convenient. It seems git works fine with getting models from huggingface. Here is an e...
git lfs clone https://huggingface.co/wanderkid/PDF-Extract-Kit 确保在克隆过程中启用了 Git LFS,以便正确下载所有大文件。 从ModelScope 下载模型 SDK下载 #首先安装modelscopepip install modelscope # 使用modelscope sdk下载模型frommodelscopeimportsnapshot_downloadmodel_dir=snapshot_download('wanderkid/PDF...
var huggingFaceContainer = new OllamaHuggingFaceContainer(hfModel); huggingFaceContainer.start(); huggingFaceContainer.commitToImage(imageName); } By providing the repository name and the model file as shown, you can run Hugging Face models in Ollama via Testcontainers. You can find an examp...
Downloading a HuggingFace model There are various ways to download models, but in my experience the huggingface_hub library has been the most reliable. The git clone method occasionally results in OOM errors for large models. Install the huggingface_hub library: pip install huggingface_hub Create ...
2. Installhuggingface-clitool. You can find the installation instructionshere huggingface-cli login After running the command, you’ll be prompted to enter your Hugging Face username and password. Make sure to enter the credentials associated with your Hugging Fa...
I'd like to know if the following solution will work: Creating a shared NFS mount, e.g./modelsand mount it on all hosts. Then, for each user, symlink their HF cache hub dir to a shared path. E.g.ln -s /models ~/.cache/huggingface/hub. ...
") self.save_path.mkdir(parents=True, exist_ok=True) self.__download_model() self.tokenizer, self.model = self.__load_model() def __repr__(self): return f"{self.__class__.__name__}(model={self.save_path})" # Download model from HuggingFace def __download_model(self) -> ...
A guided tour on how to use HuggingFace large language models on Macs with Apple Silicon - domschl/HuggingFaceGuidedTourForMac