Image-to-Text
Transformers
Safetensors
English
idefics3
image-text-to-text
chemistry
ocr
chemical-structure
document-understanding
vision-language-model
patent-analysis
smoldocling
Instructions to use docling-project/ChemicalOCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use docling-project/ChemicalOCR 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="docling-project/ChemicalOCR")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("docling-project/ChemicalOCR") model = AutoModelForMultimodalLM.from_pretrained("docling-project/ChemicalOCR", device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- ce70d35967cdf2b68ff8ed72cb9e2304eb57eea36a6abc427865333a7e2e2df6
- Size of remote file:
- 880 kB
- SHA256:
- 47dd4497899aeb8f296055c4454a785d75052be85ae15012f4e943b4d37fb18b
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