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--- |
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quantized_by: cjpais |
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base_model: vikhyatk/moondream2 |
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pipeline_tag: image-text-to-text |
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license: apache-2.0 |
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tags: |
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- llamafile |
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--- |
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A [llamafile](https://github.com/Mozilla-Ocho/llamafile) generated for [moondream2](https://huggingface.co/vikhyatk/moondream2) |
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Big thanks to [@jartine](https://huggingface.co/jartine) and [@vikhyat](https://huggingface.co/vikhyatk/moondream2) for their respective works on llamafile and moondream |
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## How to Run (on macos and linux) |
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1. Download moondream2.llamafile |
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2. `chmod +x moondream2.llamafile` - make it executable |
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3. `./moondream2.llamafile` - run the llama.cpp server |
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## Versions |
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1. [Q5_M](https://huggingface.co/cjpais/moondream2-llamafile/resolve/main/moondream2-q5_k.llamafile?download=true) |
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2. [Q8_0](https://huggingface.co/cjpais/moondream2-llamafile/resolve/main/moondream2-q8.llamafile?download=true) |
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From my short testing the Q8 is noticeably better. |
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# ORIGINAL MODEL CARD |
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moondream2 is a small vision language model designed to run efficiently on edge devices. Check out the [GitHub repository](https://github.com/vikhyat/moondream) for details, or try it out on the [Hugging Face Space](https://huggingface.co/spaces/vikhyatk/moondream2)! |
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**Benchmarks** |
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| Release | VQAv2 | GQA | TextVQA | TallyQA (simple) | TallyQA (full) | |
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| --- | --- | --- | --- | --- | --- | |
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| 2024-03-04 | 74.2 | 58.5 | 36.4 | - | - | |
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| 2024-03-06 | 75.4 | 59.8 | 43.1 | 79.5 | 73.2 | |
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| 2024-03-13 | 76.8 | 60.6 | 46.4 | 79.6 | 73.3 | |
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| **2024-04-02** (latest) | 77.7 | 61.7 | 49.7 | 80.1 | 74.2 | |
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**Usage** |
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```bash |
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pip install transformers einops |
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``` |
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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_id = "vikhyatk/moondream2" |
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revision = "2024-04-02" |
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model = AutoModelForCausalLM.from_pretrained( |
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model_id, trust_remote_code=True, revision=revision |
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) |
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tokenizer = AutoTokenizer.from_pretrained(model_id, revision=revision) |
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image = Image.open('<IMAGE_PATH>') |
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enc_image = model.encode_image(image) |
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print(model.answer_question(enc_image, "Describe this image.", tokenizer)) |
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``` |
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The model is updated regularly, so we recommend pinning the model version to a |
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specific release as shown above. |
