Mistral Quietly Unveils Mixtral 8x7B
Mistral has published a new model, but little is known about the technical details!
Created on December 8|Last edited on December 8
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Mistral AI recently announced the release of their latest model, termed "Mixtral" 8x7B. This announcement comes on the heels of their successful Mistral 7B model, which defied expectations by outperforming models with significantly more parameters. Unlike traditional strategies that focus on creating extensive and complex landing pages and promotional materials, Mistral AI took a more straightforward approach by releasing a magnet link on X/Twitter for the model.
Technical Highlights of the Mistral 7B
Mistral 7B showcased impressive capabilities with its 7.3 billion parameters. It utilized advanced techniques like Grouped-Query Attention (GQA) and Sliding Window Attention (SWA) for efficient handling of longer sequences and faster response times. The model's performance surpassed larger models in various benchmarks, including commonsense reasoning and code-related tasks. This efficiency challenges the prevailing trend in AI, where larger models with more computational power were deemed superior.
Overview of Mistral 8x7B
This new model, a "Mixture of Experts," integrates eight 7-billion parameter models. It achieves the speed of a 14-billion-parameter model (by using 2 experts). Such an architecture, utilizing selective expert deployment based on input, mirrors techniques used in advanced models like GPT-4, but with greater complexity and scale.
One of the remarkable advancements in the Mistral 8x7B model is its ability to handle a context length of 32 tokens, a significant improvement over the previous 7B model. This increased context length capability allows for more nuanced understanding and processing of information, enhancing the model's performance in tasks requiring deep contextual awareness.
Availability
The model weights are available on Huggingface or via the magnet link in the tweet below. With their efficient design and advanced capabilities, such as handling extended context lengths and utilizing a 'Mixture of Experts' framework, these models offer a glimpse into a future where AI is not only more powerful but also more accessible and efficient.
No official reports have been published about the model, and currently the weights are the main resource available.
HugggingFace: https://huggingface.co/someone13574/mixtral-8x7b-32kseqlen
The Tweet: https://twitter.com/MistralAI/status/1733150512395038967
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