Instructions to use bhadresh-savani/electra-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bhadresh-savani/electra-base-squad2 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="bhadresh-savani/electra-base-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("bhadresh-savani/electra-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("bhadresh-savani/electra-base-squad2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from bhadresh-savani/electra-base-squad2: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/bhadresh-savani/electra-base-squad2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://bhadresh-savani/electra-base-squad2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/bhadresh-savani/electra-base-squad2/resolve/main/flax_model.msgpack
436 MB
- Xet hash:
- d28d81403c36e3798b0fd8000b52e0f1d7c17683d0adc1ad576a723ed042f163
- Size of remote file:
- 436 MB
- SHA256:
- 5ff9a83a3413c0d57da7be38f7a498a5bd998f4ff8c397a9651110ba1250b94e
路
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