Image-to-Text
Transformers
Safetensors
molparser_vision_encoder_decoder
image-text-to-text
chemistry
custom_code
Instructions to use UniParser/MolParser-Mobile with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UniParser/MolParser-Mobile with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="UniParser/MolParser-Mobile", trust_remote_code=True, device_map="auto")# Load model directly from transformers import AutoModelForImageTextToText model = AutoModelForImageTextToText.from_pretrained("UniParser/MolParser-Mobile", trust_remote_code=True, dtype="auto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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datasets:
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- UniParser/MolParser-7M
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- UniParser/MolGallery
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---
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# MolParser Mobile
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```
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## 📖 Citation
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If you use this model, please cite:
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datasets:
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- UniParser/MolParser-7M
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- UniParser/MolGallery
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license: cc-by-nc-sa-4.0
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---
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# MolParser Mobile
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```
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## 📜 License
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### MolParser-Mobile Weight
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The **MolParser-Mobile model weights** are provided for **non-commercial use only**.
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For commercial licensing, please contact **fangxi@dp.tech** or open a discussion on Hugging Face.
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### MolParser Github Repo
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The **MolParser** library (including E-SMILES post-processing and rendering) is available at https://github.com/dptech-corp/MolParser and is licensed under the **Apache License 2.0**, which permits commercial use, modification, and distribution, provided that the license and copyright notices are retained.
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**Note:** Model weights, datasets, and third-party dependencies are subject to their respective licenses.
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## 📖 Citation
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If you use this datasets in your work, please cite:
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```
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@inproceedings{fang2025molparser,
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title={Molparser: End-to-end visual recognition of molecule structures in the wild},
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author={Fang, Xi and Wang, Jiankun and Cai, Xiaochen and Chen, Shangqian and Yang, Shuwen and Tao, Haoyi and Wang, Nan and Yao, Lin and Zhang, Linfeng and Ke, Guolin},
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booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
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pages={24528--24538},
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year={2025}
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}
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```
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