Image-to-Text
Transformers
Safetensors
Japanese
English
sarashina2_vision
text-generation
multimodal
ocr
document-understanding
vision-language
custom_code
Instructions to use subhash4face/sarashina2.2-ocr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use subhash4face/sarashina2.2-ocr 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="subhash4face/sarashina2.2-ocr", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("subhash4face/sarashina2.2-ocr", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 4d6be29e216feadd8271ab9f107f5d216b817ce2f59ef7df6e23bd609c2ec844
- Size of remote file:
- 786 kB
- SHA256:
- b7e80cab271d1cc76836166f497dd44a3c02a62c0e39ec3673d18df960c2789e
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