
Recent advancements in AI technology have led to significant improvements in large language models, particularly the Llama3 series. Notable developments include the introduction of several new models such as Hermes 2 Pro Llama 3, Llama 3 OpenBio LLM for the medical domain, and Llama3-ChatQA-1.5-8B by Nvidia. These models have shown remarkable performance, with some fine-tuned versions scoring higher than the Llama-3-70B and achieving top ranks in MMLU/GSM8K benchmarks on the Huggingface leaderboard. Companies like Groq Inc. and AIatMeta have also contributed to these advancements, with Groq Inc. setting new standards for throughput and AIatMeta introducing models with extended context lengths capable of perfect retrieval scores for NIAH.
Nice - LLama-3-70B with 1048k context length. trained on 34M tokens for this stage, and ~430M tokens total for all stages, which is < 0.003% of Llama-3's original pre-training data. https://t.co/8PQjIF5UT0
We’re going back 2 back! 🔥 Introducing the first 1M context window @AIatMeta Llama-3 70B to pair with the our Llama-3 8B model that we launched last week on @huggingface. Our 1M context window 70B model landed a perfect score on NIAH and we’re excited about the results that… https://t.co/d8g8hEKm5r
We’re going back 2 back! 🔥 Introducing the first 1M context window @AIatMeta Llama-3 70B to pair with the 1M context window Llama-3 8B that we launched last week on @huggingface! Our 1M context window 70B model landed a perfect score on NIAH and we’re excited about the results… https://t.co/y1ieIUCaO8






