baidu/Unlimited-OCR
image-text-to-text model by baidu
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Model card & documentation
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Unlimited OCR Works Welcome the Era of One-shot Long-horizon Parsing. Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.12.3 + CUDA12.9： Please refer to the official vLLM recipe for deployment details: Recipe: https://recipes.vllm.ai/baidu/Unlimited-OCR Use the following Docker images depending on your GPU platform: Default (CUDA 13.0): For Hopper GPUs (CUDA 12.9) Set up the environment (uv-managed virtualenv). Install the local SGLang wheel first,…
Read the full model card ↗ · Preview checked 2026-10-29T11:32:59.344Z
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Model overview
baidu/Unlimited-OCR is a image-text-to-text model repository published by baidu on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-text-to-text
- Library
- transformers
- Recent downloads (30 days)
- 3,966,076
- Cumulative likes
- 4,933
- Hugging Face trending score
- 34
- Reported safetensors parameters
- 3,336,106,240
- Architecture
- UnlimitedOCRForCausalLM
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-06-19T09:40:33.000Z
- Last modified
- 2026-10-14T06:17:59.000Z
Compatibility and lineage
Reported languages: multilingual
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:51:30.840Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.