Instructions to use howey/bert_base_uncased_squad_L3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use howey/bert_base_uncased_squad_L3 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="howey/bert_base_uncased_squad_L3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("howey/bert_base_uncased_squad_L3") model = AutoModelForQuestionAnswering.from_pretrained("howey/bert_base_uncased_squad_L3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from howey/bert_base_uncased_squad_L3: direct link, hf CLI and curl.
- Browser
- Download file 180 MB
-
https://huggingface.co/howey/bert_base_uncased_squad_L3/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://howey/bert_base_uncased_squad_L3/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/howey/bert_base_uncased_squad_L3/resolve/main/flax_model.msgpack
180 MB
- Xet hash:
- 349311b62f5e7d2de532acba10c965b6d6263dec2f2301a8f77056a2c2254a77
- Size of remote file:
- 180 MB
- SHA256:
- c389ee0be39a66ef73f871c94158bc06b544bc1ad8f4f58b90dff0dacc71a5ce
路
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