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)# Load model directly from transformers import AutoModelForImageTextToText model = AutoModelForImageTextToText.from_pretrained("UniParser/MolParser-Mobile", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "image_processor_type": "MolParserImageProcessor", | |
| "model_name": "MolParser Mobile", | |
| "auto_map": { | |
| "AutoImageProcessor": "image_processing_molparser_mobile.MolParserImageProcessor" | |
| }, | |
| "image_size": 224, | |
| "do_resize": true, | |
| "do_normalize": true, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ] | |
| } | |