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🚀 Breaking News: Meta Unleashes Its Biggest Open-Source AI Model Yet – Llama 3.1 with 405 Billion Parameters!Meta has taken a giant leap forward in AI development by releasing Llama 3.1, their most powerful open-source AI model to date, boasting an

Hello Everyone, Do you think that , Meta's plan to dominate AI sector is kind of different : Firstly make it available for free and if it is totally trained then make business from it. 1. Meta doesn't public their things easily. 2. Meta avails the

Best Open Source LLM:Tencent Hunyuan-Large: The 389 Billion Parameter Model Outperforming Llama 3 and DeepSeek V2

Meta, formerly Facebook, has unveiled two new open-source AI models called Llama 3 8B and Llama 3 70B, with 8 billion and 70 billion parameters respectively. 🚀 These models outperform some rivals and spark debate over open versus closed source AI de

Meta has released Llama 3.1, the first frontier-level open source AI model, with features such as expanded context length to 128K, support for eight languages, and the introduction of Llama 3.1 405B. The model offers flexibility and control, enabli

So 🇮🇳's IT minister said, "We will soon host DeepSeek on Indian servers. It is an open-source model like LLama. Data privacy issues regarding DeepSeek can be addressed by hosting open source models on Indian servers," says Ashwini Vaishnaw. it has

Another open-source model has arrived, and it’s even better than DeepSeek-V3. The Allen Institute for AI just introduced Tülu 3 (405B) 🐫, a post-training model that is a fine-tune of Llama 3.1 405B, which outperforms DeepSeek V3.

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Meta has introduced the Llama 3.1 series of large language models (LLMs), featuring a top-tier model with 405 billion parameters, as well as smaller variants with 70 billion and 8 billion parameters. Meta claims that Llama 3.1 matches the performance

Huge announcement from Meta. Welcome Llama 3.1🔥 This is all you need to know about it: The new models: - The Meta Llama 3.1 family of multilingual large language models (LLMs) is a collection of pre-trained and instruction-tuned generative models