Llama-3.2-3B

Multilingual Large Language Model

PremiumNewProductProductivityArtificial IntelligenceMachine Learning

Llama 3.2 is a multilingual large language model (LLM) launched by Meta, featuring pre-trained and instruction-tuned generation models in sizes of 1B and 3B parameters. These models are optimized for various multilingual conversational use cases, including agent retrieval and summarization tasks. Llama 3.2 outperforms many existing open-source and closed chat models in various industry benchmarks.

Supports eight languages
including English
German
French
Italian
Portuguese
Hindi
Spanish
and Thai.
Utilizes an optimized Transformer architecture and is fine-tuned through supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF).

\The target audience for Llama 3.2 includes researchers
developers
and enterprise users who require advanced language models to develop intelligent assistants
chatbots
and other language processing applications across multiple languages.\

Used for developing multilingual chatbots to provide customer service.
Functions as a knowledge retrieval tool to help users quickly find information.
Assists users in content creation by generating articles and summaries.

Visit the Hugging Face website and search for the Llama 3.2 model.
Choose the version you wish to use
either from the transformers library or the original llama codebase.
Install the transformers library using pip
ensuring the version is at least 4.43.0.

Visit

Llama-3.2-3B Visit Over Time

Monthly Visits

17788201

Bounce Rate

44.87%

Page per Visit

5.4

Visit Duration

00:05:32

Llama-3.2-3B Visit Trend

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Llama-3.2-3B

Llama-3.2-3B Visit Over Time

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Llama-3.2-3B Alternatives

YunHu Ai — An AI assistant that creates limitless possibilities.

SmartDialogue — Explore unlimited intelligence and build a more perfect path of aggregation.

GRIN-MoE — High-performance, low-resource consumption hybrid expert model

Mistral-Small-Instruct-2409 — High-performance instruct-tuned AI model

xAI — AI to Accelerate Human Scientific Discovery

MemoRAG — A memory-based RAG framework for general-purpose applications

RAGLAB — A modular, research-oriented unified framework for retrieval-augmented generation

DeepSeek-V2.5 — An AI model integrating general and programming capabilities.

West Lake AI Model — A multimodal model with high emotional and intellectual intelligence

Reflection Llama-3.1 70B — The world's leading open-source large language model

OLMoE-1B-7B — An efficient open-source large language model.

RWKV v6 Finch 14B — RWKV v6 Finch 14B is an open-source large model that efficiently processes long texts.

C4AI Command R+ 08-2024 — A multilingual advanced dialogue generation model with 104 billion parameters.

LLM Playground — An interactive platform for loading and testing large language models.

Index-1.9B — Index-1.9B is a lightweight, open-source large language model developed independently by Bilibili.

Aya-23-8B — A multilingual instruction fine-tuned large language model

EasyEdit — User-friendly framework for knowledge editing of large language models (LLMs)

MiLM-6B — A large-scale pre-trained language model developed by Xiaomi with a parameter scale of 64 billion.

GPT-4o — GPT-4o, a flagship model capable of real-time processing of audio, visual, and textual data.

Fugaku-LLM — Fugaku-LLM is an AI model specializing in text generation.

Next AI Jobs — Discover the best AI jobs and career opportunities in artificial intelligence, machine learning, natural language processing, and data science.

Llama-3-Giraffe-70B-Instruct — A 70B parameter large language model with an effective context length of 128k.

MAP-NEO — MAP-NEO is an entirely open-source large language model offering advanced natural language processing capabilities.

Amazon Titan Text Premier — An advanced language model designed to build generative AI applications based on Retrieval Augmented Generation (RAG) and agents

phi3-Chinese — Committed to collecting and organizing the various training variants of the phi3 model from the open source community, as well as providing tutorials for training, inference, and deployment.

spRAG — A Retrieval-Augmented Generation (RAG) framework designed to address challenging queries for dense unstructured data

LLaVA++ — LLaVA++ extends the LLaVA model by integrating Phi-3 and LLaMA-3, enhancing the interaction capability between visual and language models.

Qwen1.5-110B — The first petabyte-scale open-source model in the Qwen1.5 series, supporting multilingual functionality and an efficient Transformer decoder architecture.

Snowflake Arctic — An efficient enterprise-level AI model that achieves high-quality custom models at a low cost.