Instructions to use midas/gupshup_h2e_bart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use midas/gupshup_h2e_bart with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("midas/gupshup_h2e_bart") model = AutoModelForSeq2SeqLM.from_pretrained("midas/gupshup_h2e_bart", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from midas/gupshup_h2e_bart: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/midas/gupshup_h2e_bart/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://midas/gupshup_h2e_bart/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/midas/gupshup_h2e_bart/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 3c5991fefb921c8d6113144b0b1980e6e6c77bba9e81ab039a9611f82671236e
- Size of remote file:
- 558 MB
- SHA256:
- 134537709239d56519010c29bb2e5cfb35f57ae793fd03b3d8b054ebd3c69757
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