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:
- f617208ae4d8b2dc1c05df24f75fbaf7cb75e502930c75406c97a9d6138b37d9
- Size of remote file:
- 358 kB
- SHA256:
- 01fad2931f69be3b5110816691083e7cc0eab4ce4bb8a329e735849edd504ee3
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