Update README.md

README.md

@@ -12,22 +12,17 @@ metrics:
 - r_squared
 ---
 
-# Model Card for ReactionT5-yield-prediction
-
-This is a ReactionT5 pre-trained to predict yields of reactions. You can use the demo [here](https://huggingface.co/spaces/sagawa/ReactionT5-yield-prediction).
-
-## Model Details
-
-<!-- Provide a longer summary of what this model is. -->
+# Model Card for ReactionT5v1-yield
 
+This is a ReactionT5 pre-trained to predict yields of reactions. You can use the demo [here](https://huggingface.co/spaces/sagawa/ReactionT5_task_yield).
 
 ### Model Sources
 
 <!-- Provide the basic links for the model. -->
 
 - **Repository:** https://github.com/sagawatatsuya/ReactionT5
-- **Paper [optional]:** {{ paper | default("[More Information Needed]", true)}}
-- **Demo:** https://huggingface.co/spaces/sagawa/ReactionT5-yield-prediction
+- **Paper:** https://arxiv.org/abs/2311.06708
+- **Demo:** https://huggingface.co/spaces/sagawa/ReactionT5_task_yield
 
 ## Uses
 
@@ -35,7 +30,7 @@ This is a ReactionT5 pre-trained to predict yields of reactions. You can use the
 
 ## How to Get Started with the Model
 
-Download files and use the code below to get started with the model.
+Use the code below to get started with the model.
 
 ```python
 import torch
@@ -89,8 +84,8 @@ class ReactionT5Yield(PreTrainedModel):
         return output*100
 
 
-model = ReactionT5Yield.from_pretrained('sagawa/ReactionT5-yield-prediction')
-tokenizer = AutoTokenizer.from_pretrained('sagawa/ReactionT5-yield-prediction')
+model = ReactionT5Yield.from_pretrained('sagawa/ReactionT5v1-yield')
+tokenizer = AutoTokenizer.from_pretrained('sagawa/ReactionT5v1-yield')
 inp = tokenizer(['REACTANT:CC(C)n1ncnc1-c1cn2c(n1)-c1cnc(O)cc1OCC2.CCN(C(C)C)C(C)C.Cl.NC(=O)[C@@H]1C[C@H](F)CN1REAGENT: PRODUCT:O=C(NNC(=O)C(F)(F)F)C(F)(F)F'], return_tensors='pt')
 print(model(inp)) # tensor([[19.1666]], grad_fn=<MulBackward0>)
 ```
@@ -131,15 +126,17 @@ python train.py
 | Avg. Tests 1–4| 0.69 ± 0.104  | 0.596 ± 0.251 | 0.738 ± 0.122 | 0.785 ± 0.094 | 0.741 ± 0.126 | 0.900 ± 0.031 |
 
 
-## Citation [optional]
+## Citation
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-
-## Model Card Authors [optional]
-
-{{ model_card_authors | default("[More Information Needed]", true)}}
-
-## Model Card Contact
-
-{{ model_card_contact | default("[More Information Needed]", true)}}
+arxiv link: https://arxiv.org/abs/2311.06708
+```
+@misc{sagawa2023reactiont5,  
+      title={ReactionT5: a large-scale pre-trained model towards application of limited reaction data}, 
+      author={Tatsuya Sagawa and Ryosuke Kojima},  
+      year={2023},  
+      eprint={2311.06708},  
+      archivePrefix={arXiv},  
+      primaryClass={physics.chem-ph}  
+}
+```