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Use HF papers (#38184)

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* Use hf papers

* Hugging Face papers

* doi to hf papers

* style
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Quentin Gallouédec
2025-06-13 13:07:09 +02:00
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docs/source/en/model_doc/tvp.md
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@@ -18,7 +18,7 @@ specific language governing permissions and limitations under the License.
## Overview
The text-visual prompting (TVP) framework was proposed in the paper [Text-Visual Prompting for Efficient 2D Temporal Video Grounding](https://arxiv.org/abs/2303.04995) by Yimeng Zhang, Xin Chen, Jinghan Jia, Sijia Liu, Ke Ding.
The text-visual prompting (TVP) framework was proposed in the paper [Text-Visual Prompting for Efficient 2D Temporal Video Grounding](https://huggingface.co/papers/2303.04995) by Yimeng Zhang, Xin Chen, Jinghan Jia, Sijia Liu, Ke Ding.
The abstract from the paper is the following:
@@ -29,7 +29,7 @@ This research addresses temporal video grounding (TVG), which is the process of
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/tvp_architecture.png"
alt="drawing" width="600"/>
<small> TVP architecture. Taken from the <a href="https://arxiv.org/abs/2303.04995">original paper.</a> </small>
<small> TVP architecture. Taken from the <a href="https://huggingface.co/papers/2303.04995">original paper.</a> </small>
This model was contributed by [Jiqing Feng](https://huggingface.co/Jiqing). The original code can be found [here](https://github.com/intel/TVP).
@@ -162,7 +162,7 @@ Tips:
- This implementation of TVP uses [`BertTokenizer`] to generate text embeddings and Resnet-50 model to compute visual embeddings.
- Checkpoints for pre-trained [tvp-base](https://huggingface.co/Intel/tvp-base) is released.
- Please refer to [Table 2](https://arxiv.org/pdf/2303.04995.pdf) for TVP's performance on Temporal Video Grounding task.
- Please refer to [Table 2](https://huggingface.co/papers/2303.04995) for TVP's performance on Temporal Video Grounding task.
## TvpConfig