Instructions to use KienLe21/finetune_distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KienLe21/finetune_distilbert with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="KienLe21/finetune_distilbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("KienLe21/finetune_distilbert") model = AutoModelForQuestionAnswering.from_pretrained("KienLe21/finetune_distilbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from KienLe21/finetune_distilbert: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/KienLe21/finetune_distilbert/resolve/main/training_args.bin
- Command line
-
hf download hf://KienLe21/finetune_distilbert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KienLe21/finetune_distilbert/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- cfdca99575c8d906589aa4ec92b2ef9b4801c9a1b702204c0cd38508821bb6b9
- Size of remote file:
- 5.3 kB
- SHA256:
- ba922dd7ecef1235c8053181430a70d5dad47c6c59cb03222cd6bbe2b9f992d0
路
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