FuseAI/FuseChat-Gemma-2-9B-Instruct
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FuseAI/FuseO1-DeekSeekR1-QwQ-SkyT1-32B-Preview
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deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
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BIG release by DeepSeek AI🔥🔥🔥
DeepSeek-R1 & DeepSeek-R1-Zero: two 660B reasoning models are here, alongside 6 distilled dense models (based on Llama & Qwen) for the community!
https://huggingface.co/deepseek-ai
deepseek-ai/DeepSeek-R1
✨ MIT License : enabling distillation for custom models
✨ 32B & 70B models match OpenAI o1-mini in multiple capabilities
✨ API live now! Access Chain of Thought reasoning with model='deepseek-reasoner'
DeepSeek-R1 & DeepSeek-R1-Zero: two 660B reasoning models are here, alongside 6 distilled dense models (based on Llama & Qwen) for the community!
https://huggingface.co/deepseek-ai
deepseek-ai/DeepSeek-R1
✨ MIT License : enabling distillation for custom models
✨ 32B & 70B models match OpenAI o1-mini in multiple capabilities
✨ API live now! Access Chain of Thought reasoning with model='deepseek-reasoner'
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Tried my hand at simplifying the derivations of Direct Preference Optimization.
I cover how one can reformulate RLHF into DPO. The idea of implicit reward modeling is chef's kiss.
Blog: https://huggingface.co/blog/ariG23498/rlhf-to-dpo
I cover how one can reformulate RLHF into DPO. The idea of implicit reward modeling is chef's kiss.
Blog: https://huggingface.co/blog/ariG23498/rlhf-to-dpo
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Upload necessary tokenizer
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djuna
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You can now use the "Synthetic Data Generator" at a much larger scale with your preferred inference engine: Ollama, vLLM, TGI, and serverless inference! 🔥
Install, configure, launch!
Space: argilla/synthetic-data-generator
Examples: https://github.com/argilla-io/synthetic-data-generator/tree/main/examples
Install, configure, launch!
Space: argilla/synthetic-data-generator
Examples: https://github.com/argilla-io/synthetic-data-generator/tree/main/examples
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