Published June 29, 2023
| Version 2.3
Other
Open
DECIMER V2 Models
Authors/Creators
- 1. Friedrich Schiller University, Jena
- 2. Westfälische Hochschule
Description
The latest models for DECIMER V2.0
Update V2.3
- The latest models trained on TPU V4 and uses 512 x 512 as input images
- The fine-tuned model is available for hand-drawn images.
- The latest models can now understand chemical structure depictions with R-Groups and predict SMILES
- The model was trained on images generated using RanDepict 1.1.3
- DECIMER checkpoints also made available to use for further training
For more details about implementation: https://github.com/Kohulan/DECIMER-Image_Transformer
Original Paper:
- Rajan, K., Zielesny, A. & Steinbeck, C. DECIMER 1.0: deep learning for chemical image recognition using transformers. J Cheminform 13, 61 (2021). https://doi.org/10.1186/s13321-021-00538-8
Files
DECIMER_512_checkpoints.zip
Files
(1.2 GB)
| Name | Size | Download all |
|---|---|---|
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md5:43b5ba13ae38dc86d8e8715057f4eb6e
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855.4 MB | Preview Download |
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md5:d4044b893c84d5dfe48386c0281b5d6f
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298.9 MB | Preview Download |
Additional details
References
- Rajan, K., Zielesny, A. & Steinbeck, C. DECIMER 1.0: deep learning for chemical image recognition using transformers. J Cheminform 13, 61 (2021). https://doi.org/10.1186/s13321-021-00538-8