A standalone PowerShell module provides the fastest route to local installation.
Follow the straightforward walkthrough provided below.
Everything happens automatically, including the heavy cloud asset download.
During setup, the script automatically determines and applies the best settings.
olmOCR-2-7B-1025-FP8 delivers state?of?the?art optical character recognition with a massive 7?billion parameter base, enabling unprecedented accuracy on complex document layouts. Built on the FP8 quantization scheme, it achieves a balanced trade?off between inference speed and memory footprint, making it suitable for both cloud and edge deployments. The architecture incorporates a refined vision encoder that processes high?resolution scans up to 1025?×?1025 pixels, preserving fine glyphs and contextual spacing. A dedicated language model head leverages multilingual tokenizers, supporting over 100 languages while maintaining a low error rate on cursive and printed text. Benchmark results show a 3.2?% absolute gain over the previous generation on the PubLayNet dataset, and the model is openly released under an permissive license for research and commercial use.
| Model | olmOCR-2-7B-1025-FP8 |
| Parameters | 7?B |
| Input Resolution | 1025?×?1025 |
| Quantization | FP8 |
| Supported Languages | 100+ |
| License | Permissive (Apache 2.0) |
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