Update README.md

README.md

@@ -4,6 +4,10 @@ datasets:
 - openrelay-dataset
 language:
 - en
+metrics:
+- accuracy
+- f1
+base_model: distilbert-base-uncased
 pipeline_tag: text-classification
 library_name: transformers
 tags:
@@ -17,9 +21,6 @@ tags:
 
 # openrelay-ai-v1
 
-**openrelay-ai-v1** is the first-generation AI model from [OpenRelay](https://openrelay.live/), a modern tech media and productivity platform. This model is designed to power a range of intelligent features across the OpenRelay ecosystem, including content understanding, semantic search, summarization, Q&A, recommendations, and workflow automation.
-# openrelay-ai-v1
-
 **openrelay-ai-v1** is the first-generation AI model from [OpenRelay](https://openrelay.live/), a modern tech media and productivity platform. This model is designed to power a range of intelligent features across the OpenRelay ecosystem, including content understanding, semantic search, summarization, Q&A, recommendations, and workflow automation.
 
 ---
@@ -48,9 +49,9 @@ tags:
 
 ## 🏗️ Technical Details
 
-- **Architecture:** Transformer-based (e.g., BERT, DistilBERT, or LLM, depending on pipeline)
+- **Architecture:** Transformer-based (e.g., distilbert-base-uncased, fine-tuned for OpenRelay tasks)
 - **Training Data:** Curated OpenRelay content (articles, reviews, comments), public tech/productivity datasets
-- **Supported Tasks:** Classification, summarization, retrieval, conversational AI
+- **Supported Tasks:** Text classification, summarization, semantic search, Q&A
 
 ---
 
@@ -61,7 +62,12 @@ You can load and use `openrelay-ai-v1` with Hugging Face Transformers:
 ```python
 from transformers import pipeline
 
-# Example: Summarization
+# Example: Text Classification
+classifier = pipeline("text-classification", model="openrelay/openrelay-ai-v1")
+result = classifier("Notion is a versatile productivity tool.")
+print(result)
+
+# Example: Summarization (if supported)
 summarizer = pipeline("summarization", model="openrelay/openrelay-ai-v1")
 summary = summarizer("Paste your OpenRelay article text here.")
 print(summary)
@@ -69,9 +75,15 @@ print(summary)
 
 ---
 
+## 📊 Metrics
+
+- **Accuracy** and **F1-score** measured on OpenRelay-categorized test sets and public benchmarks.
+
+---
+
 ## 📄 License
 
-[Specify your model license here, e.g. Apache-2.0 or CC-BY-4.0. Update this section.]
+This model is licensed under the [Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0).
 
 ---
 
@@ -84,7 +96,16 @@ Visit [openrelay.live](https://openrelay.live/) or follow us on [Instagram](http
 
 ## 📝 Citation
 
-If you use `openrelay-ai-v1` in your research or application, please cite this repository and the OpenRelay platform.
+If you use `openrelay-ai-v1` in your research or application, please cite this repository and the OpenRelay platform:
+
+```
+@misc{openrelay-ai-v1,
+  title={openrelay-ai-v1: OpenRelay Platform AI Model},
+  author={OpenRelay Team},
+  howpublished={\url{https://huggingface.co/openrelay/openrelay-ai-v1}},
+  year={2025}
+}
+```
 
 ---