Instructions to use hung200504/bert-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-3 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/bert-3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-3") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hung200504/bert-3: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/hung200504/bert-3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hung200504/bert-3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hung200504/bert-3/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- 9a2d157ee3888a80810db241b53df5f49f7313a29a295f5271a980ba3ed293c8
- Size of remote file:
- 265 MB
- SHA256:
- 9d35ff6ef08e60527b5d9f7839713332c1d1ae0a27b6b2e73cf5c9c48a63be6f
路
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