Instructions to use ai4bharat/MultiIndicSentenceSummarizationSS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai4bharat/MultiIndicSentenceSummarizationSS with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ai4bharat/MultiIndicSentenceSummarizationSS") model = AutoModelForSeq2SeqLM.from_pretrained("ai4bharat/MultiIndicSentenceSummarizationSS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from ai4bharat/MultiIndicSentenceSummarizationSS: direct link, hf CLI and curl.
- Browser
- Download file 1.8 MB
-
https://huggingface.co/ai4bharat/MultiIndicSentenceSummarizationSS/resolve/main/spiece.model
- Command line
-
hf download hf://ai4bharat/MultiIndicSentenceSummarizationSS/spiece.model
-
curl -L -o spiece.model https://huggingface.co/ai4bharat/MultiIndicSentenceSummarizationSS/resolve/main/spiece.model
1.8 MB
- Xet hash:
- dd32af5d3bc12c8d62271d17ebe8d0cf43ee44d84edf23ccfe2a41c45b99f14f
- Size of remote file:
- 1.8 MB
- SHA256:
- 27d922f1b9444ae05eab57f3f0a9d60d4147e905a160f07c3b08116e7b3b8c6a
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