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
File size: 374 Bytes
c81207b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"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
]
}
|