是的,您可以使用Hugging Face库加载ModelScope中的通用检查点(checkpoint)。 ModelScope的通用检查点是以PyTorch格式保存的模型权重和配置信息。Hugging Face提供了一个名为transformers的库,它支持加载和使用各种预训练模型,包括通用检查点。 以下是使用Hugging Face加载ModelScope通用检查点的示例代码: pythonCopyfrom trans...
resume_from_checkpoint(strorbool,optional) — If astr, local path to a saved checkpoint as saved by a previous instance ofTrainer. If abooland equalsTrue, load the last checkpoint inargs.output_diras saved by a previous instance ofTrainer. If present, training will resume from the model/opti...
# checkpoint = torch.hub.load_state_dict_from_url( # url='https://dl.fbaipublicfiles.com/detr/detr-r50-e632da11.pth', # map_location='cpu', # check_hash=True) # # # Remove class weights # del checkpoint["model"]["class_embed.weight"] # del checkpoint["model"]["class_embed.bi...
I had to re-install a lot of packages, but now I get an error when I try to load the tokenizer of an HuggingFace model This is my code: # Import libraries from transformers import pipeline, AutoTokenizer # Define checkpoint model_checkpoint = 'deepset/xlm-roberta-large-squad2...
It looks like you want to perform token classification (NER), but the model you are loading is just a base model that doesn't return a loss because a base model does not have a task-specific head to provide a loss (code). Instead of Automodel, you should load the wei...
cache_dir='/home/{username}/huggingface')# Set `torch_dtype=torch.float16` to load model in ...
from datasets import load_dataset raw_datasets = load_dataset("glue", "mrpc", cache_dir = '~/.cache/huggingface/dataset') raw_datasets 1. 2. 3. 4. 可以得到结果: DatasetDict({ train: Dataset({ features: ['sentence1', 'sentence2', 'label', 'idx'], ...
应该是需要修改参数的,epoch、lr、warmup吧
OSError: Unable to load weights from pytorch checkpoint file. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True. Environment info transformersversion: 2.9.0 Platform: Ubuntu 18.04 Python version: 3.7.4 ...
一旦checkpoint被保存,我们可以通过将transformers.ONNX包的--model参数指向所需的目录将其导出到ONNX: python -m transformers.onnx --model=local-pt-checkpoint onnx/ TensorFlow: from transformers import AutoTokenizer, TFAutoModelForSequenceClassification# 从hub加载tokenizer和TensorFlow weightstokenizer = AutoTo...