Instructions to use PrathameshPawar/sci_summary_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PrathameshPawar/sci_summary_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="PrathameshPawar/sci_summary_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("PrathameshPawar/sci_summary_2") model = AutoModelForMaskedLM.from_pretrained("PrathameshPawar/sci_summary_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload 15_test.json
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- Upload 15_test_1.json (2ef100fb5142b8d701760d4c7d2fd16210f1ffab) Co-authored-by: Ashwin Sharan <Ashwin0@users.noreply.huggingface.co>cb8094e
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Upload pytorch_model.bin
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Upload pytorch_model.bin
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Create tokenizer_config.json
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Create tokenizer.json
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Create config.json
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initial commit
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