Instructions to use PSW/summ-grounded-method-dialogsum-reverse-trained-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PSW/summ-grounded-method-dialogsum-reverse-trained-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PSW/summ-grounded-method-dialogsum-reverse-trained-model") model = AutoModelForSeq2SeqLM.from_pretrained("PSW/summ-grounded-method-dialogsum-reverse-trained-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from PSW/summ-grounded-method-dialogsum-reverse-trained-model: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/PSW/summ-grounded-method-dialogsum-reverse-trained-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://PSW/summ-grounded-method-dialogsum-reverse-trained-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/PSW/summ-grounded-method-dialogsum-reverse-trained-model/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 4644fb7c5ca45e24c5d55aab5ed00d2e3264ec5bbb031676f93e1e71712db8b5
- Size of remote file:
- 558 MB
- SHA256:
- fb2b98544b3a916a4741ce38b6576aaee16f4173030a0c8c1c677d98742a0cc6
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