Instructions to use SalmonAI123/Question_answering_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SalmonAI123/Question_answering_test 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="SalmonAI123/Question_answering_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SalmonAI123/Question_answering_test") model = AutoModelForQuestionAnswering.from_pretrained("SalmonAI123/Question_answering_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SalmonAI123/Question_answering_test: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/SalmonAI123/Question_answering_test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SalmonAI123/Question_answering_test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SalmonAI123/Question_answering_test/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- 97a4734cc71295d693a9555abdcfaaf1acd810379d33e58acdcdf1f3ad00654c
- Size of remote file:
- 265 MB
- SHA256:
- 62e06f259f053070597fca830f40b5df5f370740fa12d10cd5ff9fb19942095e
路
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