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- Edit this `README.md` markdown file to author your organization card.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # 🔍 OverseerAI
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+
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+ ## Mission
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+ 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.
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+
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+ ## 🌟 Our Projects
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+
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+ ### Datasets
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+ #### [BrandSafe-16k](https://huggingface.co/datasets/OverseerAI/BrandSafe-16k)
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+ A comprehensive dataset for training brand safety classification models, featuring 16 distinct risk categories:
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+ - B1-PROFANITY: Explicit language and cursing
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+ - B2-OFFENSIVE_SLANG: Informal offensive terms
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+ - B3-COMPETITOR: Competitive brand mentions
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+ - B4-BRAND_CRITICISM: Negative brand commentary
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+ - B5-MISLEADING: Deceptive or false information
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+ - B6-POLITICAL: Political content and discussions
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+ - B7-RELIGIOUS: Religious themes and references
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+ - B8-CONTROVERSIAL: Contentious topics
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+ - B9-ADULT: Adult or mature content
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+ - B10-VIOLENCE: Violent themes or descriptions
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+ - B11-SUBSTANCE: Drug and alcohol references
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+ - B12-HATE: Hate speech and discrimination
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+ - B13-STEREOTYPE: Stereotypical content
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+ - B14-BIAS: Biased viewpoints
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+ - B15-UNPROFESSIONAL: Unprofessional content
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+ - B16-MANIPULATION: Manipulative content
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+
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+ ### Models
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+
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+ #### [vision-1](https://huggingface.co/OverseerAI/vision-1)
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+ Our flagship model for brand safety classification:
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+ - Architecture: Meta Llama 3.1 (15GB)
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+ - Full precision model optimized for high accuracy
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+ - Trained on BrandSafe-16k dataset
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+ - Ideal for production deployments with high-end GPU resources
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+
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+ #### [vision-1-mini](https://huggingface.co/OverseerAI/vision-1-mini)
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+ A lightweight, optimized version of vision-1:
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+ - Size: 4.58 GiB
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+ - Architecture: Llama 3.1 8B
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+ - Quantization: GGUF V3 (Q4_K)
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+ - Optimized for Apple Silicon
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+ - Fast load time: