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--- |
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license: apache-2.0 |
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datasets: |
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- openrelay/openrelay-dataset |
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language: |
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- en |
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metrics: |
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- accuracy |
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- f1 |
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base_model: distilbert-base-uncased |
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pipeline_tag: text-classification |
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library_name: transformers |
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tags: |
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- openrelay |
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- productivity |
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- summarization |
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- semantic-search |
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- Q&A |
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- workflow |
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--- |
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# openrelay-ai-v1 |
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**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. |
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--- |
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## 🧠 Model Highlights |
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- **Content Categorization:** |
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Automatically tags and organizes articles, reviews, and resources by topic. |
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- **Semantic Search:** |
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Find tools, guides, and discussions using natural language queries. |
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- **Summarization:** |
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Generates concise summaries and key takeaways for long-form reviews and blog posts. |
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- **Sentiment Analysis:** |
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Detects the tone of reviews and community feedback. |
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- **Q&A / Chatbot:** |
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Powers instant answers to questions about tools, workflows, and platform features. |
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- **Personalization:** |
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Underpins recommendation systems for personalized content and tool suggestions. |
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--- |
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## 🏗️ Technical Details |
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- **Architecture:** Transformer-based (e.g., distilbert-base-uncased, fine-tuned for OpenRelay tasks) |
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- **Training Data:** Curated OpenRelay content (articles, reviews, comments), public tech/productivity datasets |
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- **Supported Tasks:** Text classification, summarization, semantic search, Q&A |
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--- |
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## 🚀 Usage |
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You can load and use `openrelay-ai-v1` with Hugging Face Transformers: |
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```python |
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from transformers import pipeline |
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# Example: Text Classification |
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classifier = pipeline("text-classification", model="openrelay/openrelay-ai-v1") |
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result = classifier("Notion is a versatile productivity tool.") |
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print(result) |
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# Example: Summarization (if supported) |
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summarizer = pipeline("summarization", model="openrelay/openrelay-ai-v1") |
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summary = summarizer("Paste your OpenRelay article text here.") |
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print(summary) |
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``` |
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--- |
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## 📊 Metrics |
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- **Accuracy** and **F1-score** measured on OpenRelay-categorized test sets and public benchmarks. |
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--- |
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## 📄 License |
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This model is licensed under the [Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0). |
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--- |
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## 🤗 About OpenRelay |
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OpenRelay is a tech media and productivity platform focused on tool reviews, workflow optimization, and community-powered guides. |
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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/). |
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--- |
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## 📝 Citation |
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If you use `openrelay-ai-v1` in your research or application, please cite this repository and the OpenRelay platform: |
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``` |
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@misc{openrelay-ai-v1, |
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title={openrelay-ai-v1: OpenRelay Platform AI Model}, |
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author={OpenRelay Team}, |
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howpublished={\url{https://huggingface.co/openrelay/openrelay-ai-v1}}, |
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year={2025} |
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} |
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``` |
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--- |
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**openrelay-ai-v1** marks the beginning of OpenRelay's AI-driven evolution, enabling smarter workflows and a more engaging, personalized user experience. |
