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--- |
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license: gemma |
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language: |
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- en |
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pipeline_tag: image-text-to-text |
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--- |
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# Cerule - A Tiny Mighty Vision Model |
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### Based on Google's - <span style="color: #D56c76;">Gemma-2b + SigLIP</span> |
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``` |
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ββββββββββββββββββββββ βββ ββββββ ββββββββ |
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βββββββββββββββββββββββββββ ββββββ ββββββββ |
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βββ ββββββ βββββββββββ ββββββ ββββββ |
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βββ ββββββ βββββββββββ ββββββ ββββββ |
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βββββββββββββββββββ ββββββββββββββββββββββββββββ |
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ββββββββββββββββββ βββ βββββββ ββββββββββββββββ |
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``` |
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We train and release "Cerule", a tiny yet powerful Vision Lanuage Model based on the newly released Google's [Gemma-2b](https://huggingface.co/google/gemma-2b) and Google's [SigLIP](https://huggingface.co/google/siglip-so400m-patch14-384). |
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We utilise highly efficient data selection techniques with: |
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``` |
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- Pretraining stage : 650K images (A LAION Subset) |
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- Finetuning stage : 695K images (SVIT-mix-665K modified for finetuning(Dataset SOON!)) |
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``` |
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The training setup was `4xA100's 80GB` and took ~6 hours to pretrain and ~13 hours to finetune. We modify and adapt the training code from [LLaVA](https://github.com/haotian-liu/LLaVA). |
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π¨ Training code, Data and more details to release soon! |
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--- |
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| Image | Example | |
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|-------|---------| |
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| ![astronaut](examples/astronaut.png) | **Describe the image**<br>The image is a playful and surreal depiction of a man in a space suit, sitting on a chair and holding a green beer bottle. The man is wearing a white space suit, complete with a helmet and gloves. His feet are clad in black and white shoes, and he is placed on a sandy surface. The background features a large, blue planet, with a moon and a star visible in the sky. | |
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| ![mario](examples/mario.png) | **Who are the characters in the image?**<br>The image features three characters, two of them are Mario and Luigi, and the third one is Yoshi.<br><br>**Describe the actions of the characters**<br>The Mario and Luigi characters are holding their arms out, as if they are waving. Yoshi is standing on its own, with its arms folded. | |
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| ![extreme_ironing](examples/extreme_ironing.jpg) | **What's funny about this image?**<br>The image is quite humorous as it depicts a man ironing clothes on the back of a yellow taxi cab. This is not a typical sight you'd expect to see in everyday life. | |
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## Loading the model |
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``` |
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pip install -qr https://huggingface.co/Tensoic/Cerule-v0.1/resolve/main/requirements.txt |
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``` |
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```python |
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from transformers import AutoModelForCausalLM |
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model = AutoModelForCausalLM.from_pretrained("Tensoic/Cerule-v0.1", trust_remote_code=True) |
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``` |
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## Training: |
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We will release the training code in some time. |
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### Inference: |
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Clone the following repo and following instructions for a CLI based inference. |
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https://github.com/Tensoic-AI/Cerule |
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## License |
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Model subject to Gemma(base model license) terms of use along with the underlying datasets(LAOIN and SVIT) subject to their respective licenses. All codes are Apache 2.0 |
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