Update README.md

README.md

@@ -1,11 +1,23 @@
 ---
 license: mit
+language:
+- en
+pipeline_tag: object-detection
+tags:
+- VIT
+- Cooking
+- Vegetables
+- Moondream
+- Intel
+- IPEX
 ---
 ## Development Process
 This model was created with the intention of supplmenting our mobile application as an ingredient counter. Such that a user could take an image and have AI determine whether they have the necessary ingredients to create a recipe. As a result of the straightforward usecase, we were motivated to use a lightweight model for this classification task. We were recommended Moondream by a mentor from Intel, which we fine-tuned in this project.
 
 Upon exploring potential datasets, we found that there was no existing data which included various ingredients within the same scene in addition to quantitative labeling data for each ingredient. We decided to work with a small subset of potential ingredients for our project, to minimize the volatility of our demo-model and prove the efficacy of this feature. During the Hackathon, we acquired 3 produce items and a bag of chips from a local grocery store, which we then used to capture image data and label the quantities of said items.
 
+We utilized the Jupyter server provided by Intel to fine-tune, and deployed on a IDC compute instance with a Small VM - Intel® Xeon 4th Gen ® Scalable processor to connect with our frontend.
+
 ## Model Details
 
 - **Model Name**: Moondream Fine-tuned Variant
@@ -41,4 +53,4 @@ Upon exploring potential datasets, we found that there was no existing data whic
 
 - **License**: Model released under MIT License.
 - **Contact Information**: For inquiries, contact [[email protected]](mailto:[email protected]).
-- **Acknowledgments**: Acknowledge Intel team for starter code and assistance in fine-tuning.
+- **Acknowledgments**: Acknowledge Intel team for starter code and assistance in fine-tuning.