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William Suffill

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reacted to codelion's post with 👀 2 days ago
Released 17 production-ready adaptive text classifiers that learn from just 100 examples per class and continuously improve without retraining. These models achieve 93% average accuracy across enterprise use cases like email routing, fraud detection, document classification, and support ticket categorization. Built on ModernBERT with prototype memory and elastic weight consolidation. Key benefits: 90% cost reduction vs API solutions, 90-120ms local inference, dynamic class addition, and zero vendor lock-in. All models available under adaptive-classifier organization. Install with pip install adaptive-classifier. Full technical details: https://huggingface.co/blog/codelion/enterprise-ready-classifiers Code: https://github.com/codelion/adaptive-classifier
liked a model 6 days ago
unsloth/gpt-oss-20b-GGUF
reacted to mrfakename's post with 👍 3 months ago
Hi everyone, I just launched TTS Arena V2 - a platform for benchmarking TTS models by blind A/B testing. The goal is to make it easy to compare quality between open-source and commercial models, including conversational ones. What's new in V2: - **Conversational Arena**: Evaluate models like CSM-1B, Dia 1.6B, and PlayDialog in multi-turn settings - **Personal Leaderboard**: Optional login to see which models you tend to prefer - **Multi-speaker TTS**: Random voices per generation to reduce speaker bias - **Performance Upgrade**: Rebuilt from Gradio → Flask. Much faster with fewer failed generations. - **Keyboard Shortcuts**: Vote entirely via keyboard Also added models like MegaTTS 3, Cartesia Sonic, and ElevenLabs' full lineup. I'd love any feedback, feature suggestions, or ideas for models to include. https://huggingface.co/spaces/TTS-AGI/TTS-Arena-V2
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