Meta Llama 3 8B Instruct Alternatives

Meta-Llama-3-8B-Instruct is an 8 billion parameter language model hosted on Hugging Face under the NousResearch organization. It belongs to the Llama 3 family and serves as an instruction-tuned variant intended for conversational and assistant-style applications. The model uses the LlamaForCausalLM architecture with a model type of llama. Its tokenizer configuration includes a specific chat template that structures messages with role-based headers, beginning-of-text and end-of-text tokens, and support for an add-generation-prompt flag to prepare responses from an assistant role. The configuration also defines bos_token as <|begin_of_text| and eos_token as <|eot_id|. It is delivered as a repository on the Hugging Face platform, where it can be accessed for download and use in machine learning workflows. The page indicates substantial community engagement through over two million all-time downloads. The model was created on April 18, 2024. As a foundation model, it is positioned for research, fine-tuning, and integration into local AI systems that require instruction following. The repository is part of the broader Hugging Face ecosystem for open-source machine learning models.

This is the 8B Instruct version of Meta's Llama 3.1 model, hosted by Unsloth on Hugging Face. It supports instruction following, tool use, and long context windows. The model is widely used for local inference, fine-tuning, and as a base for custom applications via the Transformers library.

This is a community-hosted version of Meta's Llama 3.1 8B Instruct model. It has been optimized for dialogue, tool calling, and following complex instructions. With a 128k context window, it is suitable for a wide range of applications including coding assistance, agentic workflows, and general chat. The model is fully open and available in multiple formats on Hugging Face.

Meta-Llama-3-70B-Instruct is the instruction-tuned version of Meta's 70 billion parameter Llama 3 model. It excels at dialogue, reasoning, and following complex instructions. The model weights are publicly available on Hugging Face and can be used with the Transformers library or optimized inference runtimes. It is intended for developers and researchers building advanced AI applications.

Llama 3.1 405B Instruct is Meta's flagship open-weights large language model. It supports advanced chat templates, tool calling, and high-quality instruction following. The model is available on Hugging Face for download and can be used with various inference frameworks and providers.

Llama-3.1-8B-Instruct is an open-source large language model developed by Meta for instruction-following and conversational AI tasks. It is designed for developers and researchers to build advanced NLP applications and is available via Hugging Face with open weights.

Llama-3.2-3B-Instruct is an open-source, instruction-tuned language model designed for text generation and conversational AI. It supports both local and API-based inference, making it ideal for developers building chatbots, virtual assistants, and other NLP applications.

Llama-3.2-1B-Instruct is an open-source, instruction-tuned language model from Meta, designed for text generation and conversational AI. It is suitable for developers and researchers building chatbots, virtual assistants, and other NLP applications.

This is a bitsandbytes 4-bit quantized version of Meta's Llama 3.1 8B Instruct model, optimized by Unsloth for faster training and inference. It includes a custom chat template supporting tools and is designed for efficient local deployment using popular inference libraries.

This is a Red Hat optimized FP8 quantized variant of Meta's Llama 3.1 8B Instruct model. It supports chat, tool calling, and code interpretation while using less memory. Targeted at enterprise and open-source developers seeking performant, locally runnable LLMs.

This is an AWQ INT4 quantized version of Meta's Llama 3.3 70B Instruct model. It enables efficient local or server-based inference while preserving most of the original model's capabilities, including tool use and reasoning. The model is hosted on Hugging Face.

This is an FP8-quantized version of Meta's Llama 3.1 70B Instruct model, published by RedHatAI. It maintains strong instruction-following capabilities while using a more memory-efficient format suitable for self-hosted deployment. The model includes a detailed chat template and is designed for production inference environments.

NousResearch/Meta-Llama-3-8B is a popular hosted copy of Meta's Llama 3 8B model on Hugging Face. It is a decoder-only transformer pretrained on a massive corpus and is suitable for text generation and fine-tuning. The model can be run locally with Transformers or through various inference providers.

Llama 3.1 8B is a text-generation model hosted on Hugging Face under the identifier meta-llama/Llama-3.1-8B. It belongs to the class of foundation models and carries the pipeline tag text-generation. The model is made available through the Hugging Face platform where it can be accessed for download and inference. It uses the transformers library and includes a tokenizer configuration with defined beginning-of-text and end-of-text tokens. Inference providers such as featherless-ai list it with live status for the text-generation task. Uploaded in July 2024 and last modified in October 2024, the model has recorded more than 26 million all-time downloads and maintains an active community presence with over two thousand likes. It appears in collections and supports integration within the broader Hugging Face ecosystem of models, datasets, and spaces. No specific licensing, pricing, or target user roles are stated on the page. The surrounding Hugging Face site promotes open source and open science as part of its mission.

Llama-3.1-8B-Instruct is an instruction-tuned version of Meta's Llama 3.1 8B model, optimized by Unsloth for faster training and inference. It supports chat templates, function calling, and various quantization formats for efficient local or cloud deployment. The model is intended for developers building custom AI applications, agents, or fine-tuned domain-specific assistants.

MaziyarPanahi/Meta-Llama-3-8B-Instruct-GGUF is a repository on Hugging Face that hosts GGUF quantized versions of Meta's Llama 3 8B Instruct model. It supplies multiple quantization files to support efficient local inference on a range of hardware. The available files include Meta-Llama-3-8B-Instruct.IQ1_M.gguf, Meta-Llama-3-8B-Instruct.IQ1_S.gguf, Meta-Llama-3-8B-Instruct.IQ2_XS.gguf, Meta-Llama-3-8B-Instruct.IQ3_XS.gguf, Meta-Llama-3-8B-Instruct.IQ4_XS.gguf, Meta-Llama-3-8B-Instruct.Q2_K.gguf, Meta-Llama-3-8B-Instruct.Q3_K_L.gguf, Meta-Llama-3-8B-Instruct.Q3_K_M.gguf, Meta-Llama-3-8B-Instruct.Q3_K_S.gguf, Meta-Llama-3-8B-Instruct.Q4_K_M.gguf, Meta-Llama-3-8B-Instruct.Q4_K_S.gguf, Meta-Llama-3-8B-Instruct.Q5_K_M.gguf, and Meta-Llama-3-8B-Instruct.Q5_K_S.gguf. These different levels allow users to select trade-offs between model size and performance. The repository also contains a chat template that defines formatting for messages with roles, beginning and end of text tokens, and assistant prompts. It is delivered as downloadable GGUF files through the Hugging Face platform. The total file size across all variants is listed as 16069403840 bytes. This format enables compatibility with inference engines that support GGUF, such as those used for running large language models locally. The repository forms part of the class of foundation models provided in quantized GGUF format for open-source use. No pricing, licensing details, or specific target audience beyond general access on Hugging Face are stated.

This is a community-quantized GGUF version of Meta's Llama 3.1 8B Instruct model, optimized for use with LM Studio and other local inference tools. It provides an instruction-tuned 8 billion parameter language model that can run efficiently on consumer CPUs and GPUs. The GGUF format enables flexible quantization levels to balance performance and resource requirements for local AI applications.

An FP8 dynamically quantized version of Meta's Llama 3.1 8B Instruct model created by RedHatAI. It maintains high performance while significantly reducing memory footprint for local or self-hosted inference. The model supports standard chat templates and is optimized for efficient deployment.

Meta-Llama-3.1-8B-Instruct-GGUF provides GGUF quantized files for Meta's Llama 3.1 8B Instruct model. It supports multiple quantization levels (Q2_K through Q8_0) for efficient local execution. The model is used by developers who want to run a capable instruction-tuned LLM on consumer-grade hardware without relying on cloud APIs.

Llama 3.2 11B Vision Instruct is an open vision-language model from Meta that can process both text and images. It supports instruction following across multimodal inputs and is distributed on Hugging Face for local and cloud inference. The model is suitable for developers building applications that require visual understanding combined with natural language generation.

Meta's Llama 3 70B is a powerful open-weight foundation model designed for a wide range of natural language tasks. It features improved reasoning, code generation, and multilingual capabilities compared to previous generations. The model is distributed on Hugging Face and supports inference through many popular frameworks and providers.

meta-llama/Llama-3.2-1B is an open-source large language model designed for advanced text generation and research. It offers API and CLI integration, making it suitable for developers building AI-powered applications and tools.

This repository contains an INT4 (w4a16) quantized version of Meta's Llama-3.1-8B-Instruct model. It enables efficient inference on hardware with limited resources while preserving most of the original model's instruction-following capabilities. The model is distributed for use with Transformers and compatible inference engines.

A quantized (w4a16) version of Meta's Llama 3.1 70B Instruct model provided by RedHatAI. It maintains the strong instruction-following and reasoning capabilities of the original while using 4-bit weights for more efficient inference. The model is compatible with standard Hugging Face and vLLM inference stacks.

This is a 4-bit quantized version of Meta's Llama 3.2 3B Instruct model, optimized by Unsloth for faster inference and lower memory usage. It maintains strong instruction-following capabilities while being suitable for deployment on laptops and modest GPUs. The model includes full chat templates and is compatible with the Hugging Face ecosystem.

This is an AWQ (INT4) quantized version of Meta's Llama 3.1 70B Instruct model, optimized for reduced memory usage while maintaining performance. It includes a detailed chat template and is suitable for local inference. The model is provided by the hugging-quants organization on Hugging Face.

This is a FP8 quantized version of Meta's Llama 3.1 8B model, published by RedHatAI. It supports multiple languages including English, German, French, and Italian. The model is compatible with the transformers library and vLLM, making it suitable for efficient text generation in production environments.