Image-to-Text
Transformers
Safetensors
dots_ocr
text-generation
ocr
document-parse
layout
table
formula
quantized
4-bit precision
custom_code
bitsandbytes
Instructions to use helizac/dots.ocr-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use helizac/dots.ocr-4bit 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="helizac/dots.ocr-4bit", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("helizac/dots.ocr-4bit", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13927c3ac9e8dd6b707ee2529187c0a8fb07e0868b9592d10c780e634be218a5
- Size of remote file:
- 11.4 MB
- SHA256:
- 904d81ff0cfa066dbc0b6a21e10ded6ebb7c2d8df14100d851f90bb7878bd5de
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