Image-to-Text
Transformers
Safetensors
mistral3
text-generation
ocr
document-understanding
vision-language
pdf
tables
forms
Eval Results
🇪🇺 Region: EU
Instructions to use lightonai/LightOnOCR-1B-1025 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lightonai/LightOnOCR-1B-1025 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="lightonai/LightOnOCR-1B-1025")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSeq2SeqLM processor = AutoProcessor.from_pretrained("lightonai/LightOnOCR-1B-1025") model = AutoModelForSeq2SeqLM.from_pretrained("lightonai/LightOnOCR-1B-1025", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -74,13 +74,13 @@ All benchmarks evaluated using **vLLM** on the Olmo-Bench.
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uv venv --python 3.12 --seed
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source .venv/bin/activate
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--torch-backend=auto \
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--extra-index-url https://wheels.vllm.ai/
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--prerelease=allow
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# if this fails try adding triton-kernels package
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'triton-kernels @ git+https://github.com/triton-lang/triton.git@v3.5.0#subdirectory=python/triton_kernels'
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uv pip install pypdfium2 pillow requests
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```
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uv venv --python 3.12 --seed
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source .venv/bin/activate
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export VLLM_COMMIT=e88bdd60d9a25d985168c9f4a60ab10095236d7c
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uv pip install vllm \
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'triton-kernels @ git+https://github.com/triton-lang/triton.git@v3.5.0#subdirectory=python/triton_kernels' \
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--torch-backend=auto \
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--extra-index-url https://wheels.vllm.ai/${VLLM_COMMIT} \
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--prerelease=allow
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uv pip install pypdfium2 pillow requests
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```
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