Improve model card: add pipeline tag, project page link, paper info, and citation

This PR improves the model card by:

* Adding the `pipeline_tag` to enable filtering on the Hugging Face Hub.
* Adding a link to the project page.
* Adding paper information.
* Adding citation details.

README.md

@@ -1,18 +1,20 @@
 ---
-license: cc-by-4.0
-datasets:
-- andaba/TEMPURA-VER
 base_model:
 - Qwen/Qwen2.5-VL-3B-Instruct
+datasets:
+- andaba/TEMPURA-VER
 library_name: transformers
+license: cc-by-4.0
 tags:
 - text-generation-inference
+pipeline_tag: video-text-to-text
 ---
+
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+This model card describes TEMPURA, a model for temporal event masked prediction and understanding for reasoning in action.
 
 ## Model Details
 
@@ -20,23 +22,21 @@ This modelcard aims to be a base template for new models. It has been generated
 
 <!-- Provide a longer summary of what this model is. -->
 
+TEMPURA enhances video temporal understanding by integrating causal reasoning with fine-grained temporal segmentation. More details can be found on the [project page](https://andy-cheng.github.io/TEMPURA/).
 
+- **Developed by:** Jen-Hao Cheng, Vivian Wang, Huayu Wang, Huapeng Zhou, Yi-Hao Peng, Hou-I Liu, Hsiang-Wei Huang, Kuang-Ming Chen, Cheng-Yen Yang, Wenhao Chai, Yi-Ling Chen, Vibhav Vineet, Qin Cai, Jenq-Neng Hwang
+- **Model type:** Video-Language Model
+- **Language(s) (NLP):** English
+- **License:** cc-by-4.0
+- **Finetuned from model:** Qwen/Qwen2.5-VL-3B-Instruct
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
+### Model Sources
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** [https://github.com/andy-cheng/TEMPURA](https://github.com/andy-cheng/TEMPURA)
+- **Paper:** [TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in Action](https://huggingface.co/papers/2505.01583)
+- **Project Page:** [https://andy-cheng.github.io/TEMPURA/](https://andy-cheng.github.io/TEMPURA/)
 
 ## Uses
 
@@ -46,36 +46,34 @@ This modelcard aims to be a base template for new models. It has been generated
 
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-[More Information Needed]
+The model can be used directly for temporal grounding and highlight detection in videos.
 
 ### Downstream Use [optional]
 
 <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
 
-[More Information Needed]
+The model can be fine-tuned for various applications requiring temporal video understanding, such as video summarization, event extraction, and question answering.
 
 ### Out-of-Scope Use
 
 <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
-[More Information Needed]
+The model may not perform well on videos with significantly different visual styles or languages compared to the training data.
 
 ## Bias, Risks, and Limitations
 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-[More Information Needed]
+The model's performance is influenced by biases present in the VER dataset. Further analysis is needed to fully characterize these biases.
 
 ### Recommendations
 
 <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+Users should be aware of potential biases in the model's outputs.
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
-
 [More Information Needed]
 
 ## Training Details
@@ -84,22 +82,19 @@ Use the code below to get started with the model.
 
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
 
-[More Information Needed]
+The model was trained on the VER dataset ([https://huggingface.co/datasets/andaba/TEMPURA-VER](https://huggingface.co/datasets/andaba/TEMPURA-VER)).
 
 ### Training Procedure
 
 <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
 
-#### Preprocessing [optional]
-
-[More Information Needed]
-
+The training procedure involves masked event prediction and video event segmentation with temporal dense captioning. See the training scripts in the repository for details.
 
 #### Training Hyperparameters
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+-   **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
 
-#### Speeds, Sizes, Times [optional]
+#### Speeds, Sizes, Times
 
 <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
 
@@ -135,8 +130,6 @@ Use the code below to get started with the model.
 
 #### Summary
 
-
-
 ## Model Examination [optional]
 
 <!-- Relevant interpretability work for the model goes here -->
@@ -149,11 +142,11 @@ Use the code below to get started with the model.
 
 Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
 
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
+-   **Hardware Type:** [More Information Needed]
+-   **Hours used:** [More Information Needed]
+-   **Cloud Provider:** [More Information Needed]
+-   **Compute Region:** [More Information Needed]
+-   **Carbon Emitted:** [More Information Needed]
 
 ## Technical Specifications [optional]
 
@@ -173,17 +166,26 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 [More Information Needed]
 
-## Citation [optional]
+## Citation
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
 **BibTeX:**
 
-[More Information Needed]
+```tex
+@article{tempura,
+       title={TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in Action}, 
+       author={Jen-Hao Cheng and Vivian Wang and Huayu Wang and Huapeng Zhou and Yi-Hao Peng and Hou-I Liu
+              and Hsiang-Wei Huang and Kuang-Ming Chen and Cheng-Yen Yang
+              and Wenhao Chai and Yi-Ling Chen and Vibhav Vineet and Qin Cai and Jenq-Neng Hwang},
+       journal={arXiv preprint arXiv:2505.01583},
+       year={2025}
+}
+```
 
 **APA:**
 
-[More Information Needed]
+Cheng, J.-H., Wang, V., Wang, H., Zhou, H., Peng, Y.-H., Liu, H.-I., Huang, H.-W., Chen, K.-M., Yang, C.-Y., Chai, W., Chen, Y.-L., Vineet, V., Cai, Q., & Hwang, J.-N. (2025). *TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in Action*. arXiv preprint arXiv:2505.01583.
 
 ## Glossary [optional]