Instructions to use ModelTC/bart-base-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-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="ModelTC/bart-base-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-squad") model = AutoModelForQuestionAnswering.from_pretrained("ModelTC/bart-base-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from ModelTC/bart-base-squad: direct link, hf CLI and curl.
- Browser
- Download file 1.12 GB
-
https://huggingface.co/ModelTC/bart-base-squad/resolve/main/optimizer.pt
- Command line
-
hf download hf://ModelTC/bart-base-squad/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ModelTC/bart-base-squad/resolve/main/optimizer.pt
1.12 GB
- Xet hash:
- 42b52c3d683bb78f293bb1062a003fef94401d41df71e3411d12cf89b2b60ecf
- Size of remote file:
- 1.12 GB
- SHA256:
- 0ec8dd92f3cd4244945c54334a432a67a4402358e9a71193ea9e8f68bf8a313b
路
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