Instructions to use hung200504/distilbert-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/distilbert-4 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="hung200504/distilbert-4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/distilbert-4") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/distilbert-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hung200504/distilbert-4: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/hung200504/distilbert-4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hung200504/distilbert-4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hung200504/distilbert-4/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- 382a9251c774540bb19e82cadb52d191f6907bc06d67e82cbb59f0cf3ae798d0
- Size of remote file:
- 265 MB
- SHA256:
- 600799dddfe840c295767302388e29e72c9a12516a0e6bb292dd69ecfa225e89
路
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