Instructions to use devvanshhh/flanT5-description-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devvanshhh/flanT5-description-generation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("devvanshhh/flanT5-description-generation") model = AutoModelForSeq2SeqLM.from_pretrained("devvanshhh/flanT5-description-generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from devvanshhh/flanT5-description-generation: direct link, hf CLI and curl.
- Browser
- Download file 616 MB
-
https://huggingface.co/devvanshhh/flanT5-description-generation/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://devvanshhh/flanT5-description-generation/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/devvanshhh/flanT5-description-generation/resolve/main/last-checkpoint/optimizer.pt
616 MB
- Xet hash:
- e31d4e3dbe271b9b2ccf275f50c173bcd5657179084e2063a4c844650e7e7efd
- Size of remote file:
- 616 MB
- SHA256:
- 72b6ff8f4fbe34ee98597fdbd9ea794f71158f338b211d878558fe285a771764
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