Instructions to use abhiBatu/MeetingSumm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abhiBatu/MeetingSumm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("abhiBatu/MeetingSumm") model = AutoModelForSeq2SeqLM.from_pretrained("abhiBatu/MeetingSumm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from abhiBatu/MeetingSumm: direct link, hf CLI and curl.
- Browser
- Download file 3.25 GB
-
https://huggingface.co/abhiBatu/MeetingSumm/resolve/main/optimizer.pt
- Command line
-
hf download hf://abhiBatu/MeetingSumm/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/abhiBatu/MeetingSumm/resolve/main/optimizer.pt
3.25 GB
- Xet hash:
- 0d4619d879ce86824125efe2d9fb68f07d463f8a27f6ee01526335c934518afd
- Size of remote file:
- 3.25 GB
- SHA256:
- 577c36d145bb8349436ce0b0f7b25c8ba8d450e949156ce39e4fe4f7ac966170
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