Instructions to use jaimin/bert-large-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaimin/bert-large-squad 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="jaimin/bert-large-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("jaimin/bert-large-squad") model = AutoModelForQuestionAnswering.from_pretrained("jaimin/bert-large-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jaimin/bert-large-squad: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/jaimin/bert-large-squad/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jaimin/bert-large-squad/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jaimin/bert-large-squad/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- 925a168c07f117c6a12167ebd7a6eca2317080b888fbd7fd01af05c12244dac0
- Size of remote file:
- 1.34 GB
- SHA256:
- a40af10cc4e4bc0256f1a7671593a2390f9f98ce37704a09ff4e6365816934de
路
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