| --- |
| license: apache-2.0 |
| pipeline_tag: image-text-to-text |
| --- |
| |
| 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 latest (**2025-06-21**) 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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| ### Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| from PIL import Image |
| |
| model = AutoModelForCausalLM.from_pretrained( |
| "vikhyatk/moondream2", |
| revision="2025-06-21", |
| trust_remote_code=True, |
| device_map={"": "cuda"} # ...or 'mps', on Apple Silicon |
| ) |
| |
| # Captioning |
| print("Short caption:") |
| print(model.caption(image, length="short")["caption"]) |
| |
| print("\nNormal caption:") |
| for t in model.caption(image, length="normal", stream=True)["caption"]: |
| # Streaming generation example, supported for caption() and detect() |
| print(t, end="", flush=True) |
| print(model.caption(image, length="normal")) |
| |
| # Visual Querying |
| print("\nVisual query: 'How many people are in the image?'") |
| print(model.query(image, "How many people are in the image?")["answer"]) |
| |
| # Object Detection |
| print("\nObject detection: 'face'") |
| objects = model.detect(image, "face")["objects"] |
| print(f"Found {len(objects)} face(s)") |
| |
| # Pointing |
| print("\nPointing: 'person'") |
| points = model.point(image, "person")["points"] |
| print(f"Found {len(points)} person(s)") |
| ``` |
|
|
| ### Changelog |
|
|
| **2025-06-21** |
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|
| (release notes coming soon) |
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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) |
| 2. Added temperature and nucleus sampling to reduce repetitive outputs |
| 3. Better OCR for documents and tables (prompt with “Transcribe the text” or “Transcribe the text in natural reading order”) |
| 4. Object detection supports document layout detection (figure, formula, text, etc) |
| 5. UI understanding (ScreenSpot F1\@0.5 up from 53.3 to 60.3) |
| 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 |
| 2. Open vocabulary image tagging |
| 3. Improved counting accuracy (e.g. CountBenchQA increased from 80 to 86.4) |
| 4. Improved text understanding (e.g. OCRBench increased from 58.3 to 61.2) |
| 5. Improved object detection, especially for small objects (e.g. COCO up from 30.5 to 51.2) |
| 6. Fixed token streaming bug affecting multi-byte unicode characters |
| 7. gpt-fast style `compile()` now supported in HF Transformers implementation |
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|
