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README.md
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# A Touch, Vision, and Language Dataset for Multimodal Alignment
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by <a href="https://max-fu.github.io">Max (Letian) Fu</a>, <a href="https://www.linkedin.com/in/gaurav-datta/">Gaurav Datta*</a>, <a href="https://qingh097.github.io/">Huang Huang*</a>, <a href="https://autolab.berkeley.edu/people">William Chung-Ho Panitch*</a>, <a href="https://www.linkedin.com/in/jaimyn-drake/">Jaimyn Drake*</a>, <a href="https://joeaortiz.github.io/">Joseph Ortiz</a>, <a href="https://www.mustafamukadam.com/">Mustafa Mukadam</a>, <a href="https://scholar.google.com/citations?user=p6DCMrQAAAAJ&hl=en">Mike Lambeta</a>, <a href="https://lasr.org/">Roberto Calandra</a>, <a href="https://goldberg.berkeley.edu">Ken Goldberg</a> at UC Berkeley, Meta AI, TU Dresden, and CeTI (*equal contribution).
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[[Paper](
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<p align="center">
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<img src="img/splash_figure_alt.png" width="800">
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For TVL-LLaMA, please request access to the pre-trained LLaMA-2 from this [form](https://llama.meta.com/llama-downloads/). In particular, we use `llama-2-7b` as the base model. The weights here contains the trained [adapter](https://arxiv.org/abs/2309.03905), the tactile encoder, and the vision encoder for the ease of loading.
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For the complete info, please take a look at the [GitHub repo](https://tactile-vlm.github.io/) to see instructions on pretraining, fine-tuning, and evaluation with these models.
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# A Touch, Vision, and Language Dataset for Multimodal Alignment
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by <a href="https://max-fu.github.io">Max (Letian) Fu</a>, <a href="https://www.linkedin.com/in/gaurav-datta/">Gaurav Datta*</a>, <a href="https://qingh097.github.io/">Huang Huang*</a>, <a href="https://autolab.berkeley.edu/people">William Chung-Ho Panitch*</a>, <a href="https://www.linkedin.com/in/jaimyn-drake/">Jaimyn Drake*</a>, <a href="https://joeaortiz.github.io/">Joseph Ortiz</a>, <a href="https://www.mustafamukadam.com/">Mustafa Mukadam</a>, <a href="https://scholar.google.com/citations?user=p6DCMrQAAAAJ&hl=en">Mike Lambeta</a>, <a href="https://lasr.org/">Roberto Calandra</a>, <a href="https://goldberg.berkeley.edu">Ken Goldberg</a> at UC Berkeley, Meta AI, TU Dresden, and CeTI (*equal contribution).
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[[Paper](https://tactile-vlm.github.io/files/tvl.pdf)] | [[Project Page](https://tactile-vlm.github.io/)] | [[Checkpoints](https://huggingface.co/mlfu7/Touch-Vision-Language-Models)] | [[Dataset](https://huggingface.co/datasets/mlfu7/Touch-Vision-Language-Dataset)] | [[Citation](#citation)]
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<p align="center">
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<img src="img/splash_figure_alt.png" width="800">
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For TVL-LLaMA, please request access to the pre-trained LLaMA-2 from this [form](https://llama.meta.com/llama-downloads/). In particular, we use `llama-2-7b` as the base model. The weights here contains the trained [adapter](https://arxiv.org/abs/2309.03905), the tactile encoder, and the vision encoder for the ease of loading.
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For the complete info, please take a look at the [GitHub repo](https://tactile-vlm.github.io/) to see instructions on pretraining, fine-tuning, and evaluation with these models.
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## Citation
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Please give us a star 🌟 on Github to support us!
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Please cite our work if you find our work inspiring or use our code in your work:
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```
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@article{fu2024tvl,
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title={A Touch, Vision, and Language Dataset for Multimodal Alignment},
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author={Letian Fu and Gaurav Datta and Huang Huang and William Chung-Ho Panitch and Jaimyn Drake and Joseph Ortiz and Mustafa Mukadam and Mike Lambeta and Roberto Calandra and Ken Goldberg},
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journal={arXiv preprint arXiv:2401.14391},
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year={2024}
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}
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```
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