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README.md

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-title: README
-emoji: 🐨
-colorFrom: blue
-colorTo: red
-sdk: static
-pinned: false
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-# 🔍 OverseerAI
+# Union Street
 
-## Mission
-OverseerAI is dedicated to advancing open-source AI safety and content moderation tools. We develop state-of-the-art models and datasets for brand safety classification, making content moderation more accessible and efficient for developers and organizations.
+Union Street is a personal AI lab focused on local models, agent infrastructure, and practical open-source AI systems.
 
-## 🌟 Our Projects
+Current work centers on:
 
-### Datasets
-#### [BrandSafe-16k](https://huggingface.co/datasets/OverseerAI/BrandSafe-16k)
-A comprehensive dataset for training brand safety classification models, featuring 16 distinct risk categories:
+- local-first model serving on Apple Silicon and GPU infrastructure
+- agent tooling, evals, and long-context workflows
+- post-training experiments for useful, candid, technically capable assistants
+- small open releases from the Union Street lab
 
-| Category | Description |
-|----------|-------------|
-| B1-PROFANITY | Explicit language and cursing |
-| B2-OFFENSIVE_SLANG | Informal offensive terms |
-| B3-COMPETITOR | Competitive brand mentions |
-| B4-BRAND_CRITICISM | Negative brand commentary |
-| B5-MISLEADING | Deceptive or false information |
-| B6-POLITICAL | Political content and discussions |
-| B7-RELIGIOUS | Religious themes and references |
-| B8-CONTROVERSIAL | Contentious topics |
-| B9-ADULT | Adult or mature content |
-| B10-VIOLENCE | Violent themes or descriptions |
-| B11-SUBSTANCE | Drug and alcohol references |
-| B12-HATE | Hate speech and discrimination |
-| B13-STEREOTYPE | Stereotypical content |
-| B14-BIAS | Biased viewpoints |
-| B15-UNPROFESSIONAL | Unprofessional content |
-| B16-MANIPULATION | Manipulative content |
+Selected projects:
 
-### Models
+- **Helios Rabbit**: an experimental Helios identity LoRA for Qwopus/Qwen3.5 MoE.
+- **UnionBench**: local evals for speed, values, reasoning, and long-horizon coding work.
 
-#### [vision-1](https://huggingface.co/OverseerAI/vision-1)
-Our flagship model for brand safety classification:
-- Architecture: Meta Llama 3.1 (15GB)
-- Full precision model optimized for high accuracy
-- Trained on BrandSafe-16k dataset
-- Ideal for production deployments with high-end GPU resources
-
-#### [vision-1-mini](https://huggingface.co/OverseerAI/vision-1-mini)
-A lightweight, optimized version of vision-1:
-- Size: 4.58 GiB
-- Architecture: Llama 3.1 8B
-- Quantization: GGUF V3 (Q4_K)
-- Optimized for Apple Silicon
-- Fast load time: 3.27s
-- Efficient memory usage: 4552.80 MiB CPU / 132.50 MiB Metal
-- Perfect for local deployment and smaller compute resources
-
-## 💡 Use Cases
-- Content moderation for social media platforms
-- Brand safety monitoring for advertising
-- User-generated content filtering
-- Real-time content classification
-- Safe content recommendation systems
-
-## 🤝 Contributing
-We welcome contributions from the community! Whether it's:
-- Improving model accuracy
-- Expanding the dataset
-- Optimizing for different hardware
-- Adding new classification categories
-- Reporting issues or suggesting improvements
-
-## 📫 Contact
-- GitHub: [OverseerAI](https://github.com/OverseerAI)
-- HuggingFace: [OverseerAI](https://huggingface.co/OverseerAI)
-
-## 📜 License
-Our models are released under the Llama 3.1 license, and our datasets are available under open-source licenses to promote accessibility and innovation in AI safety.
-
----
-*OverseerAI - Making AI Safety Accessible and Efficient*
+Website: [unionstreet.ai](https://unionstreet.ai)

upload_org_card.sh

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+#!/usr/bin/env bash
+set -euo pipefail
+
+CARD_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+
+hf repo create UnionStreet/README --type space --space-sdk static --public --exist-ok
+hf upload UnionStreet/README "$CARD_DIR" . --repo-type space