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...
hfd <model_id> [--exclude exclude_pattern] [--hf_username username] [--hf_token token] [--tool wget|aria2c] [-x threads] [--dataset] Description: Downloads a model or dataset from Hugging Face using the provided model ID. Parameters: model_id The Hugging Face model ID in the form...
model = AutoModelForMaskedLM.from_pretrained("bert‑base‑uncased") When you run this code for the first time, you will see a download bar appear on screen. Seethis post(disclaimer: I gave one of the answers) if you want to find the actual folder where Huggingface stores their models...
结合第一步的相对地址填入参数【model_addr】中 创建Hub_download.py文件代码内容如下: 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_nam...
In 1 code., I have uploaded hugging face 'transformers.trainer.Trainer' based model using save_pretrained() function In 2nd code, I want to download this uploaded model and use it to make predictions. I need help in this step - How to download the uploaded model & then make a pre...
然而如果你用的huggingface-cli download gpt2 --local-dir /data/gpt2下载,即使你把模型存储到了自己指定的目录,但是你仍然可以简单的用模型的名字来引用他。即: AutoModelForCausalLM.from_pretrained("gpt2") 原理是因为huggingface工具链会在.cache/huggingface/下维护一份模型的符号链接,无论你是否指定了模型的...
目前，我遇到过两个与HuggingFace cache相关的问题。一个是关于datasets库的问题。在使用load_dataset函数...
def download(url, path=None, overwrite=False, sha1_hash=None): """Download an given URL """Download a given URL Parameters --- url : str URL to download url : dict, url for downloading the model, with keys: repo_id, subfolder, filename path : str, optional Destination path to st...
snapshot_download(repo_id=model_id, local_dir="Qwen2.5-3B", local_dir_use_symlinks=False, revision="main") 1. 2. 3. 4. 复制 步骤2:转换为llama.cpp格式 2.1 准备环境 git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp ...
Open Same question. Thank you. If you don't want/cannot to use the built-in download/caching method, you can download both files manually, save them in a directory and rename them respectivelyconfig.jsonandpytorch_model.bin Then you can load the model usingmodel = BertModel.from_pretrained...