Feature Extraction
Transformers
Safetensors
English
qwen2_vl
bnb-my-repo
4-bit precision
bitsandbytes
Instructions to use nielsgl/olmOCR-7B-0225-preview-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nielsgl/olmOCR-7B-0225-preview-bnb-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nielsgl/olmOCR-7B-0225-preview-bnb-4bit")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("nielsgl/olmOCR-7B-0225-preview-bnb-4bit") model = AutoModel.from_pretrained("nielsgl/olmOCR-7B-0225-preview-bnb-4bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f982f62e5a7f6dcc5488ca3995fbe180b7fdf579678a7e5c6bdbe12acc294b8
- Size of remote file:
- 4.81 GB
- SHA256:
- 6a23480f572673b59850ebaf2382138c81b03a5d7abb34237db2e3bd262acf20
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