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Sudeep Pillai PRO

spillai

AI & ML interests

Self-supervised learning, Few-shot learning, Computer Vision, Robotics

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reacted to nwaughachukwuma's post with 🔥 7 days ago
# VLM Run Gateway: Run GLM-OCR, DeepSeek-OCR-2, and Dots.mocr with an OpenAI Compatible API Open-weight OCR VLMs have advanced significantly over the past year, yet most teams still rely on frontier VLMs for document parsing because researching, evaluating, and deploying the right models remains challenging. So we built VLM Run Gateway: one OpenAI-compatible endpoint for open-weight OCR and VLM models. If you’re using frontier VLMs primarily for OCR/document parsing, open-weight OCR models can be dramatically cheaper and often very accurate. With a one-line change, you can switch between open-weight OCR VLMs (DeepSeek OCR 2, GLM-OCR, dots.mocr, Paddle OCR VL, PP-OCRv6, etc.) and process 100K+ pages for under $60. Try it out quickly via the CLI: ``` uvx vlmrun gw models uvx vlmrun config set --api-key '<VLMRUN_API_KEY>' # anon-user, rate-limited uvx vlmrun gw chat <doc>.pdf -m zai-org/glm-ocr uvx vlmrun gw chat <doc>.pdf -m zai-org/glm-ocr --json-mode uvx vlmrun gw chat <doc>.pdf -m deepseek-ai/deepseek-ocr-2 uvx vlmrun gw chat <doc>.pdf -m rednote-hilab/dots.mocr uvx vlmrun gw chat <doc>.pdf -m paddleocr/pp-ocrv6 ``` OpenAI SDK: ``` client = OpenAI( base_url="https://gateway.vlm.run/v1/openai", api_key="<VLMRUN_API_KEY>", ) response = client.chat.completions.create( model="rednote-hilab/dots.mocr", messages=[{ "role": "user", "content": [{ "type": "document_url", "document_url": {"url": "https://.../invoice.pdf"}, }], }], extra_body={"document_dpi": 72}, ) ``` Docs: https://docs.vlm.run/gateway Catalog: https://docs.vlm.run/gateway/models MCP: https://docs.vlm.run/gateway/mcp-server Colab Quickstart: https://colab.research.google.com/drive/1RkuVIyuc5Po-UlcSlFyJCam5tjCm9IHM?usp=sharing Read the full post here: https://huggingface.co/blog/vlm-run/intro-to-vlmrun-gateway
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