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--- |
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license: apache-2.0 |
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pipeline_tag: image-text-to-text |
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--- |
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Moondream is a small vision language model designed to run efficiently everywhere. |
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[Website](https://moondream.ai/) / [Demo](https://moondream.ai/playground) / [GitHub](https://github.com/vikhyat/moondream) |
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This repository contains the 2025-04-14 **int4** release of Moondream, as well as [historical releases](https://huggingface.co/vikhyatk/moondream2/blob/main/versions.txt). The model is updated frequently, so we recommend specifying a revision as shown below if you're using it in a production application. |
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Make sure to install the requirements: |
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``` |
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pip install -r https://depot.moondream.ai/transformers/requirements.txt |
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``` |
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### Usage |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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from PIL import Image |
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model = AutoModelForCausalLM.from_pretrained( |
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"moondream/moondream-2b-2025-04-14-4bit", |
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trust_remote_code=True, |
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# Uncomment to run on GPU. |
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device_map={"": "cuda"} |
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) |
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# Captioning |
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print("Short caption:") |
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print(model.caption(image, length="short")["caption"]) |
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print("\nNormal caption:") |
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for t in model.caption(image, length="normal", stream=True)["caption"]: |
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# Streaming generation example, supported for caption() and detect() |
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print(t, end="", flush=True) |
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print(model.caption(image, length="normal")) |
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# Visual Querying |
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print("\nVisual query: 'How many people are in the image?'") |
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print(model.query(image, "How many people are in the image?")["answer"]) |
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# Object Detection |
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print("\nObject detection: 'face'") |
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objects = model.detect(image, "face")["objects"] |
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print(f"Found {len(objects)} face(s)") |
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# Pointing |
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print("\nPointing: 'person'") |
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points = model.point(image, "person")["points"] |
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print(f"Found {len(points)} person(s)") |
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``` |
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### Changelog |
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**int4-2025-04-15** ([full release notes](https://moondream.ai/blog/moondream-2025-04-14-release)) |
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1. Moondream uses a whole lot less memory (4.12 down to 2.47GB) |
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2. Small device get a big speed up (44.54 to 67.84 tok/sec on a RTX 4050 Mobile) |
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3. Improved spatial understanding (RealWorldQA up from 58.3 to 60.13) |
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**2025-04-15** ([full release notes](https://moondream.ai/blog/moondream-2025-04-14-release)) |
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1. Improved chart understanding (ChartQA up from 74.8 to 77.5, 82.2 with PoT) |
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2. Added temperature and nucleus sampling to reduce repetitive outputs |
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3. Better OCR for documents and tables (prompt with “Transcribe the text” or “Transcribe the text in natural reading order”) |
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4. Object detection supports document layout detection (figure, formula, text, etc) |
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5. UI understanding (ScreenSpot F1\@0.5 up from 53.3 to 60.3) |
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6. Improved text understanding (DocVQA up from 76.5 to 79.3, TextVQA up from 74.6 to 76.3) |
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**2025-03-27** ([full release notes](https://moondream.ai/blog/moondream-2025-03-27-release)) |
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1. Added support for long-form captioning |
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2. Open vocabulary image tagging |
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3. Improved counting accuracy (e.g. CountBenchQA increased from 80 to 86.4) |
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4. Improved text understanding (e.g. OCRBench increased from 58.3 to 61.2) |
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5. Improved object detection, especially for small objects (e.g. COCO up from 30.5 to 51.2) |
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6. Fixed token streaming bug affecting multi-byte unicode characters |
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7. gpt-fast style `compile()` now supported in HF Transformers implementation |
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