Dialogue-oriented instruction tuning
According to the model card, the Llama 3 instruction-tuned models are optimized for dialogue use cases in 8B and 70B sizes.
Open Source Model Profile · meta-llama
Meta-Llama-3-70B-Instruct is a 70.55B-parameter Llama-family text-generation fine-tune from meta-llama. According to the model card, it is an instruction-tuned Llama 3 variant optimized for dialogue use cases.
Meta-Llama-3-70B-Instruct is published by meta-llama as a llama text-generation model. The captured configuration identifies LlamaForCausalLM and Safetensors metadata reports 70,553,706,496 parameters. According to the model card, it belongs to the Llama 3 family in 8B and 70B instruction-tuned variants, with tuned versions using supervised fine-tuning and reinforcement learning with human feedback.
According to the model card, the Llama 3 instruction-tuned models are optimized for dialogue use cases in 8B and 70B sizes.
According to the model card, the tuned versions use supervised fine-tuning and reinforcement learning with human feedback to align for helpfulness and safety.
According to the model card, both 8B and 70B versions use an 8k context length and Grouped-Query Attention for inference scalability.
According to the model card, the 70B instruction-tuned variant is reported at 82.0 on MMLU, 81.7 on HumanEval, 93.0 on GSM-8K, and 50.4 on MATH.
Source: meta-llama/Meta-Llama-3-70B-Instruct
Captured: Unknown. Processed: 2026-09-07T19:34:51.858219+00:00.
Model Details Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks. Further, in developing these models, we took great care to optimize helpfulness and safety. Model developers Meta Variations Llama 3 comes in two sizes — 8B and 70B parameters — in pre-trained and instruction tuned variants. Input Models input text only. Output Models generate text…
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