Instructions to use nlpunibo/bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpunibo/bert 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="nlpunibo/bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nlpunibo/bert") model = AutoModelForQuestionAnswering.from_pretrained("nlpunibo/bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from nlpunibo/bert: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/nlpunibo/bert/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://nlpunibo/bert@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/nlpunibo/bert/resolve/refs%2Fpr%2F1/flax_model.msgpack
436 MB
- Xet hash:
- 253e49f0f7d7579203b8ec77959ce10b6b1bc71940575f58660597a5ec82e252
- Size of remote file:
- 436 MB
- SHA256:
- 5e689fb64997fc77fbfb092591e507b06d36f1f8827a9a898f8ab37c729423d5
路
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