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sagawa
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ReactionT5v2-forward

Text2Text Generation
Transformers
Safetensors
English
t5
chemistry
SMILES
product
text-generation-inference
Inference Endpoints
Model card Files Community
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@@ -85,8 +85,8 @@ python train_without_duplicates.py \
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  | Molecular Transformer| USPTO_MIT | USPTO_MIT | 88.8 | 92.6 | – | 94.4 |
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  | T5Chem | USPTO_MIT | USPTO_MIT | 90.4 | 94.2 | – | 96.4 |
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  | CompoundT5 | USPTO_MIT | USPTO_MIT | 86.6 | 89.5 | 90.4 | 91.2 |
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- | ReactionT5 (This model) | - | USPTO_MIT | 92.8 | 95.6 | 96.4 | 97.1 |
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- | ReactionT5 | USPTO_MIT | USPTO_MIT | 97.5 | 98.6 | 98.8 | 99.0 |
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  Performance comparison of Compound T5, ReactionT5, and other models in product prediction.
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  | Molecular Transformer| USPTO_MIT | USPTO_MIT | 88.8 | 92.6 | – | 94.4 |
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  | T5Chem | USPTO_MIT | USPTO_MIT | 90.4 | 94.2 | – | 96.4 |
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  | CompoundT5 | USPTO_MIT | USPTO_MIT | 86.6 | 89.5 | 90.4 | 91.2 |
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+ | [ReactionT5 (This model)](https://huggingface.co/sagawa/ReactionT5v2-forward) | - | USPTO_MIT | 92.8 | 95.6 | 96.4 | 97.1 |
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+ | [ReactionT5](https://huggingface.co/sagawa/ReactionT5v2-forward-USPTO_MIT) | USPTO_MIT | USPTO_MIT | 97.5 | 98.6 | 98.8 | 99.0 |
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  Performance comparison of Compound T5, ReactionT5, and other models in product prediction.
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