liujch1998
/

vera

@@ -24,19 +24,19 @@ A score of 1 means the statement is correct according to commonsense, and a scor
 This score is calibrated, so a score between 0 and 1 can be interpreted as Vera's confidence that the statement is correct.
 - **Developed by:** Jiacheng Liu, Wenya Wang, Dianzhuo Wang, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi
-- **Shared by [optional]:** Jiacheng Liu
 - **Model type:** Transformers
 - **Language(s) (NLP):** English
 - **License:** MIT
-- **Finetuned from model [optional]:** T5-v1.1-XXL
-### Model Sources [optional]
 <!-- Provide the basic links for the model. -->
 - **Repository:** <https://github.com/liujch1998/vera>
-- **Paper [optional]:** <https://arxiv.org/abs/2305.03695>
-- **Demo [optional]:** <https://huggingface.co/spaces/liujch1998/vera>
 ## Uses
@@ -48,7 +48,7 @@ This score is calibrated, so a score between 0 and 1 can be interpreted as Vera'
 Vera is intended to predict the correctness of commonsense statements.
-### Downstream Use [optional]
 <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
@@ -66,12 +66,6 @@ Vera is a research prototype and may make mistakes. Do not use for making critic
 See the **Limitations and Ethics Statement** section of our paper.
-### 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.
 ## How to Get Started with the Model
 Use the code below to get started with the model.
@@ -100,7 +94,7 @@ with torch.no_grad():
 You may also refer to <https://huggingface.co/spaces/liujch1998/vera/blob/main/app.py#L27-L98> for implementation.
-## Citation [optional]
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
@@ -118,4 +112,4 @@ You may also refer to <https://huggingface.co/spaces/liujch1998/vera/blob/main/a
 ## Model Card Contact
-Jiacheng Liu

 This score is calibrated, so a score between 0 and 1 can be interpreted as Vera's confidence that the statement is correct.
 - **Developed by:** Jiacheng Liu, Wenya Wang, Dianzhuo Wang, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi
+- **Shared by:** [Jiacheng (Gary) Liu](https://liujch1998.github.io/)
 - **Model type:** Transformers
 - **Language(s) (NLP):** English
 - **License:** MIT
+- **Finetuned from model:** T5-v1.1-XXL
+### Model Sources
 <!-- Provide the basic links for the model. -->
 - **Repository:** <https://github.com/liujch1998/vera>
+- **Paper:** <https://arxiv.org/abs/2305.03695>
+- **Demo:** <https://huggingface.co/spaces/liujch1998/vera>
 ## Uses
 Vera is intended to predict the correctness of commonsense statements.
+### Downstream Use
 <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
 See the **Limitations and Ethics Statement** section of our paper.
 ## How to Get Started with the Model
 Use the code below to get started with the model.
 You may also refer to <https://huggingface.co/spaces/liujch1998/vera/blob/main/app.py#L27-L98> for implementation.
+## Citation
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 ## Model Card Contact
+[Jiacheng (Gary) Liu](https://liujch1998.github.io/)