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Mixtral, a state-of-the-art Mixture of Experts (MoE) model by Mistral AI, has demonstrated exceptional performance across various NLP tasks. Integrating Mixtral into Keras Hub would provide users with an efficient and scalable language model within the TensorFlow/Keras ecosystem.
Why is this needed?
✅ High Efficiency: Mixtral is a sparse model, enabling cost-effective inference while maintaining high-quality outputs.
✅ State-of-the-Art Performance: It has achieved strong results on multiple NLP benchmarks.
✅ Ease of Access: Adding Mixtral to Keras Hub will make it more accessible to deep learning practitioners using TensorFlow/Keras.
Proposed Solution
🔹 Implement Mixtral as a KerasNLP model.
🔹 Provide pre-trained weights compatible with TensorFlow/Keras.
🔹 Include examples and documentation to help users fine-tune and utilize Mixtral efficiently within Keras workflows.
Add Mixtral Model to Keras Hub
Description
Mixtral, a state-of-the-art Mixture of Experts (MoE) model by Mistral AI, has demonstrated exceptional performance across various NLP tasks. Integrating Mixtral into Keras Hub would provide users with an efficient and scalable language model within the TensorFlow/Keras ecosystem.
Why is this needed?
Proposed Solution
References
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