Update README.md

README.md

@@ -11,18 +11,17 @@ This model was pre-trained on the entire CHAMMI-75 dataset using the bag of chan
 The utility of this model is to be used in single-cell analysis of microscopic imaging.
 
 
-- **Developed by:** Vidit Agrawal, Juan Caicedo
-- **Funded by:** NSF, Meta AI
+- **Developed by:** Vidit Agrawal, John Peters, Juan Caicedo
 - **Shared by:** [Caicedo Lab]
-- **Model type:** [More Information Needed]
+- **Model type:** Vision Transformer Small
 - **License:** MIT License
 
-### Model Sources [optional]
+### Model Sources
 
 <!-- Provide the basic links for the model. -->
 
 - **Repository:** https://github.com/CaicedoLab/CHAMMI-75
-- **Paper**
+<!-- - **Paper** -->
 - **Demo:** https://github.com/CaicedoLab/CHAMMI-75/tree/main/aws-tutorials
 
 ## Uses
@@ -60,48 +59,17 @@ Use the code below to get started with the model.
 
 We have utilized the DINO model. 
 
-#### Preprocessing [optional]
+#### Preprocessing
 
 [More Information Needed]
 
 ## Evaluation
 
 <!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
+specify all 6 benchmarks, and point to them. Point to the paper?
 
 #### Summary
 
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
 ## Environmental Impact
 
 <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
@@ -114,50 +82,24 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 - **Compute Region:** Private Infrastructure
 - **Carbon Emitted:** 324 kg CO2
 
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-The model is a ViT Small trained on 2500 Nvidia A6000 GPU hours.
-
-### Compute Infrastructure
+## Technical Specifications
 
-The model was trained on a multi-node system with 2 nodes, each containing 7 GPUs.
 
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
+The model is a ViT Small trained on 2500 Nvidia A6000 GPU hours. The model was trained on a multi-node system with 2 nodes, each containing 7 GPUs.
 
-## 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:**
+<!-- **BibTeX:** -->
 
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
+<!-- **APA:** -->
 
-## Model Card Authors [optional]
+## Model Card Authors
 
-Vidit Agrawal, John Peters, Tyler N. Thompson, Mohammad Vali Sanian, Chau Pham, Nikita Moshkov, Arshad Kazi, Aditya Pillai, Jack Freeman, Byunguk Kang, Samouil L. Farhi, Ernest Fraenkel, Ron M. Stewart, Lassi Paavolainen, Bryan A. Plummer, Juan C. Caicedo
+Vidit Agrawal, John Peters, Juan C. Caicedo
 
 ## Model Card Contact
 
-vagrawal22@wisc.edu, juan.caicedo@wisc.edu
+vagrawal22@wisc.edu, jgpeters3@wisc.edu, juan.caicedo@wisc.edu