Xavier Martinet - Principales líderes e innovadores de IA | Perfiles, hitos y proyectos - xix.ai
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Xavier Martinet
Xavier Martinet

Xavier Martinet

Ingeniero de Investigación, Meta AI
Año de nacimiento  1990
Nacionalidad  French

Hito importante

2019 Se unió a Meta AI

Trabajó en la infraestructura de AI en Meta

Artículo de LLaMA 2023

Artículo de investigación de LLaMA coescrito

Despliegue de LLaMA 3.1 2024

Despliegue asistido de LLaMA 3.1 en plataformas en la nube

Producto de IA

The Llama 4 models are auto-regressive language models that use a mixture-of-experts (MoE) architecture and incorporate early fusion for native multimodality.

Llama3.1 are multilingual and have a significantly longer context length of 128K, state-of-the-art tool use, and overall stronger reasoning capabilities.

Llama 3.1 405B is the first openly available model that rivals the top AI models when it comes to state-of-the-art capabilities in general knowledge, steerability, math, tool use, and multilingual translation.

The Llama 3.2 3B models support context length of 128K tokens and are state-of-the-art in their class for on-device use cases like summarization, instruction following, and rewriting tasks running locally at the edge.

Llama3.1 are multilingual and have a significantly longer context length of 128K, state-of-the-art tool use, and overall stronger reasoning capabilities.

Llama3 is Meta's latest open-source large language model, trained on a 15T corpus, supports an 8K context length, and has been optimized for effectiveness and safety.

Llama 3.1 405B is the first openly available model that rivals the top AI models when it comes to state-of-the-art capabilities in general knowledge, steerability, math, tool use, and multilingual translation.

Llama3.1 are multilingual and have a significantly longer context length of 128K, state-of-the-art tool use, and overall stronger reasoning capabilities.

Llama3.1 are multilingual and have a significantly longer context length of 128K, state-of-the-art tool use, and overall stronger reasoning capabilities.

The Llama 3.2 3B models support context length of 128K tokens and are state-of-the-art in their class for on-device use cases like summarization, instruction following, and rewriting tasks running locally at the edge.

The Llama 4 models are auto-regressive language models that use a mixture-of-experts (MoE) architecture and incorporate early fusion for native multimodality

Llama3 is Meta's latest open-source large language model, trained on a 15T corpus, supports an 8K context length, and has been optimized for effectiveness and safety.

The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks we tested.

Llama 3.1 405B is the first openly available model that rivals the top AI models when it comes to state-of-the-art capabilities in general knowledge, steerability, math, tool use, and multilingual translation.

Llama3.1 are multilingual and have a significantly longer context length of 128K, state-of-the-art tool use, and overall stronger reasoning capabilities.

The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks we tested.

The Llama 4 models are auto-regressive language models that use a mixture-of-experts (MoE) architecture and incorporate early fusion for native multimodality

Llama3.1 are multilingual and have a significantly longer context length of 128K, state-of-the-art tool use, and overall stronger reasoning capabilities.

Llama3.1 are multilingual and have a significantly longer context length of 128K, state-of-the-art tool use, and overall stronger reasoning capabilities.

The Llama 3.2 3B models support context length of 128K tokens and are state-of-the-art in their class for on-device use cases like summarization, instruction following, and rewriting tasks running locally at the edge.

Llama3.1 are multilingual and have a significantly longer context length of 128K, state-of-the-art tool use, and overall stronger reasoning capabilities.

Perfil personal

Apoyó la infraestructura de LLaMA para el entrenamiento de modelos a gran escala.

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