Llama-3.2-1B-Instruct-QLORA_INT4_EO8

Model Information The Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. They outperform many of the available open source and closed chat models on common industry benchmarks. Model Developer: Meta Model Architecture: Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety. Training Data Params Input modalities Output modalities Context Length GQA Shared Embeddings Token count Knowledge cutoff Llama 3.2 (text only) A new mix of publicly available online data. 1B (1.23B) Multilingual Text Multilingual Text and code 128k Yes Yes Up to 9T tokens December 2023 3B (3.21B) Multilingual Text Multilingual Text and code Llama 3.2 Quantized (text only) A new mix of publicly available online data. 1B (1.23B) Multilingual Text Multilingual Text and code 8k Yes Yes Up to 9T tokens December 2023 3B (3.21B) Multilingual Text Multilingual Text and code Supported Languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai are officially supported. Llama 3.2 has been trained on a broader collection of languages than these 8 supported languages. Developers may fine-tune Llama 3.2 models for languages beyond these supported languages, provided they comply with the Llama 3.2 Community License and the Acceptable Use Policy. Developers are always expected to ensure that their deployments, including those that involve additional languages, are completed safely and responsibly. Llama 3.2 Model Family: Token counts refer to pretraining data only. All model versions use Grouped-Query Attention (GQ