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README.md
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tags:
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- multimodal
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- multilingual
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- llm
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- vision
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- vlm
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- translation
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language:
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base_model:
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- Unbabel/Tower-Plus-2B
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pipeline_tag: image-text-to-text
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---
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# Model Card for TowerVision
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This model card covers the TowerVision family, including the 2B and 9B parameter versions, both in their instruct-tuned (it) and pretrained (pt) variants, with the latter not undergoing instruction tuning.
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- **Point of Contact**: X (add some email here)
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- **License**: Apache 2.0
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- **Model Family**: TowerVision (2B, 9B variants)
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- **Context length**: 8192 tokens
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- **Languages**: 20+ languages including European, Asian, and other language families
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## How to Use TowerVision
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### Quick Start with Transformers
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<details open>
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For errors or additional questions about details in this model card, contact the research team.
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## Terms of Use
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We hope that the release of this model will make community-based research efforts more accessible by releasing the weights of highly performant multilingual vision-language models to researchers all over the world.
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This model is governed by the Apache 2.0 License.
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## Acknowledgments
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TowerVision builds upon the excellent work of:
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tags:
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- multimodal
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- multilingual
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- vlm
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- translation
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language:
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base_model:
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- Unbabel/Tower-Plus-2B
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pipeline_tag: image-text-to-text
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license: cc-by-nc-sa-4.0
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---
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# Model Card for TowerVision
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This model card covers the TowerVision family, including the 2B and 9B parameter versions, both in their instruct-tuned (it) and pretrained (pt) variants, with the latter not undergoing instruction tuning.
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- **Model Family**: TowerVision (2B, 9B variants)
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- **Context length**: 8192 tokens
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- **Languages**: 20+ languages including European, Asian, and other language families
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## How to Use TowerVision
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When using the model, make sure your prompt is formated correctly!
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Also, we recommend using **bfloat16** rather than **fp32/16**
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### Quick Start with Transformers
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<details open>
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For errors or additional questions about details in this model card, contact the research team.
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## Acknowledgments
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TowerVision builds upon the excellent work of:
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