from_pretrained("internlm/internlm2-chat-7b", trust_remote_code=True, cache_dir='/home/{username}/huggingface') # Set `torch_dtype=torch.float16` to load model in float16, otherwise it will be loaded as float32 and cause OOM Error. model = AutoModelForCausalLM.from_pretrained("intern...
AAA/BBB是HugglingFace官网复制的模型的名字,比如说hfl/rbt3或者distilbert/distilbert-base-uncased-finetuned-sst-2-english之类的。 也可以使用--local-dir指定下载路径。 然后调用模型就是按照官网教的方式: # 使用Auto方法 from transformers import AutoModel, AutoTokenizer model = AutoModel.from_pretrained(...
The issue only manifests if you're trying to load a local model and the model doesn't have the safetensors weights. Here is how to reproduce: @Narsilhi , could you please tell us more detail about how to mount the model locally? if the parameters are in ~/.cache/huggingface/hub/mo...
OSError: Can't load tokenizer for'bert-base-chinese'. If you were trying to load it from'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'bert-base-chinese' is the correct path to a directory containing all relevant ...
I have a pre-trained model that I want to load it from its state-dict. I use the following code: model_class = getattr(transformers, 'XLMRobertaForSequenceClassification') model = model_class.from_pretrained( pretrained_model_name_or_path=None, config=model_type, num_labels=num_classes, ...
Check out the [`~PreTrainedModel.from_pretrained`] method to load the model weights. Returns The return block should be introduced with the Returns: prefix, followed by a line return and an indentation. The first line should be the type of the return, followed by a line return. No need...
model:model可以是一个集成了transformers.PreTrainedMode或者torch.nn.module的模型,官方提到trainer对 transformers.PreTrainedModel进行了优化,建议使用。transformers.PreTrainedModel,用于可以通过自己继承这个父类来实现huggingface的model自定义,自定义的过程和torch非常相似,这部分放到huggingface的自定义里讲。
ChatGLM-6B 是一个开源的、支持中英双语的对话语言模型，基于 General Language Model (GLM) 架构，具有 62 亿参数。结合模型量化技术，用户可以在消费级的显卡上进行本地部署（INT4 量化级别下最低只需 6GB 显存）。将
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File "/opt/conda/lib/python3.10/site-packages/llamafactory/model/loader.py", line 69, in load_tokenizer tokenizer = AutoTokenizer.from_pretrained( File "/opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py", line 834, in from_pretrained ...