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Alibaba released Qwen2.5-Max, a Mixture-of-Expert language model pretrained on over 20 trillion tokens, which is now available through Alibaba Cloud's API and Qwen Chat. The model outperformed DeepSeek V3 on Arena-Hard, LiveBench, LiveCodeBench, and GPQA-Diamond benchmarks while achieving competitive results on MMLU-Pro. The API is accessible through Alibaba Cloud with OpenAI-compatible endpoints for developers to integrate the model into applications.
A research team launched Open-R1 to reproduce DeepSeek-R1's training methods after DeepSeek released a reasoning model that matched OpenAI's o1 performance but kept the training code and datasets proprietary. The project will systematically reconstruct the data pipeline and reinforcement learning approach across three steps, starting with distilling datasets from DeepSeek-R1 and progressing to pure RL training on math, code, and reasoning tasks. This open-source reproduction aims to let any researcher fine-tune existing language models into reasoning models using the shared datasets and training recipes.
Hugging Face integrated four serverless inference providers—fal, Replicate, SambaNova, and Together AI—directly into its Hub platform and client SDKs to offer unified access to model inference. PRO users receive $2 monthly in inference credits that work across all providers, with no markup added to standard provider API rates. Users can now run models like DeepSeek-R1 through their preferred provider using either their own API keys or Hugging Face's routing service, with configuration available through the website, Python, JavaScript, or HTTP calls.
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