Instructions to use ammar00200/quant_summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ammar00200/quant_summary with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ammar00200/quant_summary") model = AutoModelForSeq2SeqLM.from_pretrained("ammar00200/quant_summary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.pt from ammar00200/quant_summary: direct link, hf CLI and curl.
- Browser
- Download file 620 MB
-
https://huggingface.co/ammar00200/quant_summary/resolve/main/model.pt
- Command line
-
hf download hf://ammar00200/quant_summary/model.pt
-
curl -L -o model.pt https://huggingface.co/ammar00200/quant_summary/resolve/main/model.pt
620 MB
- Xet hash:
- 4045953b3d432235c658373c6696495674cb0c7b47c568d49610765251e3081b
- Size of remote file:
- 620 MB
- SHA256:
- dee534c9ffa037ef47e726e87be9d220a6c2927ca29f978c4d415404b2a742d3
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