Meta-Llama-3.1-8B-Instruct-AWQ-INT4
Maintainer: hugging-quants
51
๐งช
| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
Create account to get full access
Model overview
The Meta-Llama-3.1-8B-Instruct model is a community-driven quantized version of the original meta-llama/Meta-Llama-3.1-8B-Instruct model released by Meta AI. This repository contains a quantized version of the model using AutoAWQ from FP16 down to INT4 precision, with a group size of 128.
Similar quantized models include the Meta-Llama-3.1-70B-Instruct-AWQ-INT4 and Meta-Llama-3.1-8B-Instruct models, which provide lower bit-depth versions of the original 8B and 70B Llama 3.1 Instruct models.
Model inputs and outputs
Inputs
- Multilingual Text: The model accepts text input in multiple languages including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
- Code: In addition to natural language, the model can also process code snippets as input.
Outputs
- Multilingual Text: The model generates output text in the same set of supported languages as the input.
- Code: The model can generate code in response to prompts.
Capabilities
The Meta-Llama-3.1-8B-Instruct model is a powerful text-to-text model capable of a wide range of natural language processing tasks. It has been optimized for multilingual dialogue use cases and outperforms many open-source and commercial chatbots on common industry benchmarks.
What can I use it for?
The Meta-Llama-3.1-8B-Instruct model can be used for a variety of applications, such as building multilingual chatbots, virtual assistants, and language generation tools. The quantized version offers significant space and memory savings compared to the original FP16 model, making it more accessible for deployment on resource-constrained devices.
Things to try
Some interesting things to try with the Meta-Llama-3.1-8B-Instruct model include generating multilingual responses, translating between supported languages, and using the model to assist with coding tasks. The quantized version's improved inference speed may also enable new use cases that require real-time text generation.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
Related Models
๐ฟ
Meta-Llama-3.1-70B-Instruct-AWQ-INT4
68
The meta-llama/Meta-Llama-3.1-70B-Instruct-AWQ-INT4 model is a quantized version of the original meta-llama/Meta-Llama-3.1-70B-Instruct model, which is a large language model developed by Meta AI. This model has been quantized using AutoAWQ from FP16 down to INT4 precision, reducing the memory footprint and computational requirements. The Llama 3.1 collection of models includes versions in 8B, 70B, and 405B parameter sizes, with the instruction-tuned models optimized for multilingual dialogue use cases. Model inputs and outputs Inputs Multilingual text**: The model can accept text input in multiple languages, including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. Code**: In addition to natural language, the model can also handle code input. Outputs Multilingual text**: The model can generate text output in the same supported languages as the inputs. Code**: The model can generate code output in addition to natural language. Capabilities The meta-llama/Meta-Llama-3.1-70B-Instruct-AWQ-INT4 model is a powerful text generation model with capabilities across a wide range of tasks, including language understanding, reasoning, code generation, and more. It has demonstrated strong performance on benchmarks like MMLU, ARC-Challenge, and HumanEval, outperforming many available open-source and commercial models. What can I use it for? This model can be used for a variety of natural language processing and generation tasks, such as: Chatbots and virtual assistants**: The instruction-tuned version of the model is well-suited for building helpful, multilingual chatbots and virtual assistants. Content generation**: The model can be used to generate high-quality text content in multiple languages, such as articles, stories, or marketing copy. Code generation**: The model's ability to generate code makes it useful for building code completion or programming assistance tools. Multilingual applications**: The model's support for multiple languages allows it to be used in building truly global, multilingual applications. Things to try Some interesting things to explore with this model include: Experimenting with different prompting and input sequences to see the range of outputs the model can generate. Evaluating the model's performance on specialized tasks or benchmarks relevant to your use case. Trying out the model's code generation capabilities by providing programming prompts and observing the quality of the output. Exploring the model's multilingual capabilities by testing it with input and output in different supported languages.
Updated Invalid Date
๐
Meta-Llama-3.1-8B-Instruct
2.0K
The Meta-Llama-3.1-8B-Instruct is a family of multilingual large language models (LLMs) developed by Meta that are pretrained and instruction tuned for various text-based tasks. The Meta Llama 3.1 collection includes models in 8B, 70B, and 405B parameter sizes, all optimized for multilingual dialogue use cases. The 8B instruction tuned model outperforms many open-source chat models on common industry benchmarks, while the larger 70B and 405B versions offer even greater capabilities. Model inputs and outputs Inputs Multilingual text input Outputs Multilingual text and code output Capabilities The Meta-Llama-3.1-8B-Instruct model has strong capabilities in areas like language understanding, knowledge reasoning, and code generation. It can engage in open-ended dialogue, answer questions, and even write code in multiple languages. The model was carefully developed with a focus on helpfulness and safety, making it suitable for a wide range of commercial and research applications. What can I use it for? The Meta-Llama-3.1-8B-Instruct model is intended for use in commercial and research settings across a variety of domains and languages. The instruction tuned version is well-suited for building assistant-like chatbots, while the pretrained models can be adapted for tasks like content generation, summarization, and creative writing. Developers can also leverage the model's outputs to improve other models through techniques like synthetic data generation and distillation. Things to try One interesting aspect of the Meta-Llama-3.1-8B-Instruct model is its multilingual capabilities. Developers can fine-tune the model for use in languages beyond the core set of English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai that are supported out-of-the-box. This opens up a wide range of possibilities for building conversational AI applications tailored to specific regional or cultural needs.
Updated Invalid Date
๐ผ๏ธ
Meta-Llama-3.1-70B-Instruct
393
The Meta-Llama-3.1-70B is a part of the Meta Llama 3.1 collection of multilingual large language models (LLMs) developed by Meta. This 70B parameter model is a pretrained and instruction-tuned generative model that supports text input and text output in multiple languages, including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. It was trained on a new mix of publicly available online data and utilizes an optimized transformer architecture. Similar models in the Llama 3.1 family include the Meta-Llama-3.1-8B and Meta-Llama-3.1-405B, which vary in their parameter counts and performance characteristics. All Llama 3.1 models use Grouped-Query Attention (GQA) for improved inference scalability. Model inputs and outputs Inputs Multilingual Text**: The Meta-Llama-3.1-70B model accepts text input in any of the 8 supported languages. Multilingual Code**: In addition to natural language, the model can also process code snippets in various programming languages. Outputs Multilingual Text**: The model can generate text output in any of the 8 supported languages. Multilingual Code**: The model is capable of producing code output in addition to natural language. Capabilities The Meta-Llama-3.1-70B model is designed for a variety of natural language generation tasks, including assistant-like chat, translation, and even code generation. Its strong performance on industry benchmarks across general knowledge, reasoning, reading comprehension, and other domains demonstrates its broad capabilities. What can I use it for? The Meta-Llama-3.1-70B model is intended for commercial and research use in multiple languages. Developers can leverage its text generation abilities to build chatbots, virtual assistants, and other language-based applications. The model's versatility also allows it to be adapted for tasks like content creation, text summarization, and even data augmentation through synthetic data generation. Things to try One interesting aspect of the Meta-Llama-3.1-70B model is its ability to handle multilingual inputs and outputs. Developers can experiment with using the model to translate between the supported languages, or to generate text that seamlessly incorporates multiple languages. Additionally, the model's strong performance on coding-related benchmarks suggests that it could be a valuable tool for building code-generating assistants or integrating code generation capabilities into various applications.
Updated Invalid Date
โ๏ธ
Meta-Llama-3.1-405B-Instruct-FP8
152
The Meta-Llama-3.1-405B-Instruct-FP8 is a large language model (LLM) developed by Meta. It is part of the Meta Llama 3.1 collection of multilingual LLMs, which includes models in 8B, 70B, and 405B sizes. The Llama 3.1 instruction-tuned text-only models are optimized for multilingual dialogue use cases and outperform many available open-source and closed-chat models on common industry benchmarks. The Llama 3.1 models use an auto-regressive architecture with supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety. The 405B version is the largest model in the Llama 3.1 family and supports 8 languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. According to the provided information, the Meta-Llama-3.1-405B-Instruct and Meta-Llama-3.1-8B are similar models in the Llama 3.1 collection, with the former being a larger instruction-tuned model and the latter a smaller base model. Model inputs and outputs Inputs Multilingual text Outputs Multilingual text and code Capabilities The Meta-Llama-3.1-405B-Instruct-FP8 model is capable of generating high-quality multilingual text and code, with strong performance on a variety of benchmarks covering general language understanding, reasoning, coding, and math tasks. It outperforms many other available models on these metrics, particularly in the instruction-tuned versions. What can I use it for? The Llama 3.1 model collection is intended for commercial and research use in multiple languages. The instruction-tuned text-only models are well-suited for assistant-like chat applications, while the pretrained models can be adapted for a variety of natural language generation tasks. The models also support the ability to leverage their outputs to improve other models, such as through synthetic data generation and distillation. Things to try Developers can explore using the Meta-Llama-3.1-405B-Instruct-FP8 model for multilingual dialogue and language generation tasks, taking advantage of its strong performance on benchmarks. It may also be interesting to investigate how the model's outputs can be used to enhance other natural language processing systems through techniques like data augmentation and model distillation.
Updated Invalid Date