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:
- adbe196871b53d6651af76eb2237ae13ea05c3c90125251c914a606b3546b3dd
- Size of remote file:
- 795 MB
- SHA256:
- 3b930052e718a6a0a4262e9fdd891e0c264feb4028deec7a421dc7f3325d07e6
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