Instructions to use gp-tar4/QA_FineTuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gp-tar4/QA_FineTuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="gp-tar4/QA_FineTuned")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("gp-tar4/QA_FineTuned") model = AutoModelForQuestionAnswering.from_pretrained("gp-tar4/QA_FineTuned") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c2212633522d7c71ce125e3c98519b25bf01ba9c62419e39db009508c815db0
- Size of remote file:
- 4.86 kB
- SHA256:
- a5da3fa51b41210bbf9b9a7ee1fd21d970f62e5406dffb4bbda1b06cec3e4046
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