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---
license: apache-2.0
datasets:
- openrelay/openrelay-dataset
language:
- en
metrics:
- accuracy
- f1
base_model: distilbert-base-uncased
pipeline_tag: text-classification
library_name: transformers
tags:
- openrelay
- productivity
- summarization
- semantic-search
- Q&A
- workflow
---
# 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.
---
## 🧠 Model Highlights
- **Content Categorization:**
Automatically tags and organizes articles, reviews, and resources by topic.
- **Semantic Search:**
Find tools, guides, and discussions using natural language queries.
- **Summarization:**
Generates concise summaries and key takeaways for long-form reviews and blog posts.
- **Sentiment Analysis:**
Detects the tone of reviews and community feedback.
- **Q&A / Chatbot:**
Powers instant answers to questions about tools, workflows, and platform features.
- **Personalization:**
Underpins recommendation systems for personalized content and tool suggestions.
---
## 🏗️ Technical Details
- **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:** Text classification, summarization, semantic search, Q&A
---
## 🚀 Usage
You can load and use `openrelay-ai-v1` with Hugging Face Transformers:
```python
from transformers import pipeline
# 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)
```
---
## 📊 Metrics
- **Accuracy** and **F1-score** measured on OpenRelay-categorized test sets and public benchmarks.
---
## 📄 License
This model is licensed under the [Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0).
---
## 🤗 About OpenRelay
OpenRelay is a tech media and productivity platform focused on tool reviews, workflow optimization, and community-powered guides.
Visit [openrelay.live](https://openrelay.live/) or follow us on [Instagram](https://instagram.com/openrelay_ig), [X](https://x.com/openrelay_x), [YouTube](https://www.youtube.com/@openrelay), [LinkedIn](https://www.linkedin.com/showcase/openrelay), [Threads](https://www.threads.com/@openrelay_ig), and [Facebook](https://www.facebook.com/openrelay/).
---
## 📝 Citation
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}
}
```
---
**openrelay-ai-v1** marks the beginning of OpenRelay's AI-driven evolution, enabling smarter workflows and a more engaging, personalized user experience. |