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NVIDIA's GTC 2025 Announcement for Physical AI Developers: New Open Models and Datasets
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NVIDIA's GTC 2025 Announcement for Physical AI Developers: New Open Models and Datasets
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My 1 year of work summarized.
TLDR: by carefully curating datasets we can fix misinformation in AI. Then we can use that to measure misinformation in other AI.
https://huggingface.co/blog/etemiz/building-a-beneficial-ai
TLDR: by carefully curating datasets we can fix misinformation in AI. Then we can use that to measure misinformation in other AI.
https://huggingface.co/blog/etemiz/building-a-beneficial-ai
Boom! cc @cfahlgren1
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Introducing ๐ OneSQL-v0.1๐ฅณ, our first text-to-SQL model based on Qwen2.5-Coder. This model has achieved an EX score of 63.33 on the BIRD leaderboard (https://bird-bench.github.io/).
The model family includes 7B and 32B,
onekq-ai/onesql-v01-qwen-67d8e3eb1611c5532bb90c5f
and can be also found on Ollama (https://ollama.com/onekq/OneSQL-v0.1-Qwen)
My goal is to make OneSQL the most usable open-weights model for text-to-SQL. I'm currently working on best practices to help users use this model the right away and avoid pitfalls. After that, I plan to train the next version to push for a higher EX score.
Enjoy this model and feel free to share comments/questions ๐ค
The model family includes 7B and 32B,
onekq-ai/onesql-v01-qwen-67d8e3eb1611c5532bb90c5f
and can be also found on Ollama (https://ollama.com/onekq/OneSQL-v0.1-Qwen)
My goal is to make OneSQL the most usable open-weights model for text-to-SQL. I'm currently working on best practices to help users use this model the right away and avoid pitfalls. After that, I plan to train the next version to push for a higher EX score.
Enjoy this model and feel free to share comments/questions ๐ค
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New 3D models from Tencent Hunyuan are now available on the hub ๐ฅ
โจ Hunyuan3D-2mv: multiview shape model for high quality generation
โจ Hunyuan3D-2mini: 0.6B lightweight model for efficient workflows
Model:
tencent/Hunyuan3D-2mv
tencent/Hunyuan3D-2mini
Demo:
tencent/Hunyuan3D-2mv
โจ Hunyuan3D-2mv: multiview shape model for high quality generation
โจ Hunyuan3D-2mini: 0.6B lightweight model for efficient workflows
Model:
tencent/Hunyuan3D-2mv
tencent/Hunyuan3D-2mini
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tencent/Hunyuan3D-2mv
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At Rapidata, we compared DeepL with LLMs like DeepSeek-R1, Llama, and Mixtral for translation quality using feedback from over 51,000 native speakers. Despite the costs, the performance makes it a valuable investment, especially in critical applications where translation quality is paramount. Now we can say that Europe is more than imposing regulations.
Our dataset, based on these comparisons, is now available on Hugging Face. This might be useful for anyone working on AI translation or language model evaluation.
Rapidata/Translation-deepseek-llama-mixtral-v-deepl
Our dataset, based on these comparisons, is now available on Hugging Face. This might be useful for anyone working on AI translation or language model evaluation.
Rapidata/Translation-deepseek-llama-mixtral-v-deepl
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