Transformers
PyTorch
English
t5
text2text-generation
chemistry
SMILES
product
text-generation-inference
Instructions to use sagawa/ReactionT5v1-forward with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagawa/ReactionT5v1-forward with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sagawa/ReactionT5v1-forward") model = AutoModelForSeq2SeqLM.from_pretrained("sagawa/ReactionT5v1-forward", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d4405c9a311137a115a23b63845a93d855a3187b41d63f03865d865c0697cb0
- Size of remote file:
- 3.44 kB
- SHA256:
- db46b1d0ebe5b1897143f0695c4b59742eb1f11c25b7d39c6a68241acec9cf2d
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