Mistral AI unveiled Mixtral 8x7B, a language model based on Sparse Mixture of Experts (SMoE), licensed under Apache 2.0. It excels in multilingual understanding, code production, and mathematics, outperforming Llama 2 70B. Mixtral 8x7B – Instruct, optimized for instructions, also impressed in human review benchmarks. Both models are accessible under Apache 2.0, with Megablocks CUDA kernel enhancements.
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Mistral AI Introduces Mixtral 8x7B: a Sparse Mixture of Experts (SMoE) Language Model Transforming Machine Learning
In a recent research, Mistral AI has unveiled Mixtral 8x7B, a language model based on the new Sparse Mixture of Experts (SMoE) model with open weights. Licensed under the Apache 2.0 license, Mixtral serves as a decoder model.
Key Features of Mixtral 8x7B:
- Dynamically selects parameter groups for token processing
- Efficiently increases model’s parameter space while controlling costs and latency
- Pre-trained using multilingual data with a 32k token context size
- Outperforms Llama 2 70B in multilingual understanding, code production, and mathematics
- Effective in recovering data from context window of 32k tokens
Assessment and Practical Applications:
Mixtral has been extensively evaluated in various categories such as math, code, reading comprehension, common sense thinking, world knowledge, and popular aggregated findings. Additionally, Mistral has introduced Mixtral 8x7B – Instruct, a conversation model optimized for instructions, which has shown superior performance in human review benchmarks.
Application and Licensing:
Mixtral 8x7B and Mixtral 8x7B – Instruct are licensed under the Apache 2.0 license, enabling both commercial and academic use. The team has modified the vLLM project by adding Megablocks CUDA kernels for effective inference.
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