A supplied HuggingChat capture shows “ML Intern” alongside text reading “mode on papers · training · spaces · datasets · eval · hub.”
A supplied capture of HuggingChat shows an “ML Intern” label with accompanying text that reads “mode on papers · training · spaces · datasets · eval · hub.”
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A supplied capture of HuggingChat shows an “ML Intern” label with accompanying text that reads: “ML Intern, mode on papers · training · spaces · datasets · eval · hub.”
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Quentin Gallouédec wrote that 1 million trainings a week is the next goal and framed post-training as a step toward a less centralized AI ecosystem. Hugging Face later reposted the post.
Liquid AI says d1 is the first model to outperform Jev on Hugging Face’s Decision Index. It also claims wins on multilingual evaluations and greater resistance to prompt injection.
