Meta-Llama-3-8B-Instruct-GGUF
Maintainer: NousResearch
109
🤯
| Property | Value |
|---|---|
| Model Link | View 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-3-8B-Instruct model is part of the Meta Llama 3 family of large language models (LLMs) developed and released by Meta. This 8 billion parameter model is a pretrained and instruction-tuned generative text model optimized for dialogue use cases. The Llama 3 models outperform many open-source chat models on common industry benchmarks while prioritizing helpfulness and safety.
Similar models in the Llama 3 family include the Meta-Llama-3-8B and Meta-Llama-3-70B variants, which come in 8 billion and 70 billion parameter sizes respectively. All Llama 3 models use an optimized transformer architecture and leverage techniques like supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences.
Model inputs and outputs
Inputs
- Text: The
Meta-Llama-3-8B-Instructmodel takes text as input.
Outputs
- Text and code: The model generates text and code outputs.
Capabilities
The Meta-Llama-3-8B-Instruct model is capable of engaging in open-ended dialogue, answering questions, and assisting with a variety of natural language tasks. Its instruction-tuning makes it well-suited for assistant-like chat applications that require helpfulness and safety. The model can also be fine-tuned for specialized use cases beyond dialogue.
What can I use it for?
The Meta-Llama-3-8B-Instruct model is intended for commercial and research use in English. Developers can leverage it to build chatbots, question-answering systems, and other language AI applications that require a helpful and safe assistant. The pretrained model can also be adapted for natural language generation tasks beyond dialogue.
Things to try
Try using the Meta-Llama-3-8B-Instruct model to engage in open-ended conversations and see how it responds. You can also experiment with providing it with specific tasks or prompts to gauge its capabilities. Remember to leverage the provided safety resources when deploying the model in production to mitigate potential risks.
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
🤔
Meta-Llama-3-8B-Instruct
61
The Meta-Llama-3-8B-Instruct is part of the Meta Llama 3 family of large language models (LLMs) developed by NousResearch. This 8 billion parameter model is a pretrained and instruction-tuned generative text model, optimized for dialogue use cases. The Llama 3 instruction-tuned models are designed to outperform many open-source chat models on common industry benchmarks, while prioritizing helpfulness and safety. Model inputs and outputs Inputs The model takes text input only. Outputs The model generates text and code. Capabilities The Meta-Llama-3-8B-Instruct model is a versatile language generation tool that can be used for a variety of natural language tasks. It has been shown to perform well on common industry benchmarks, outperforming many open-source chat models. The instruction-tuned version is particularly adept at engaging in helpful and informative dialogue. What can I use it for? The Meta-Llama-3-8B-Instruct model is intended for commercial and research use in English. The instruction-tuned version can be used to build assistant-like chat applications, while the pretrained model can be adapted for a range of natural language generation tasks. Developers should review the Responsible Use Guide and consider incorporating safety tools like Meta Llama Guard 2 when deploying the model. Things to try Experiment with the model's dialogue capabilities by providing it with different types of prompts and personas. Try using the model to generate creative writing, answer open-ended questions, or assist with coding tasks. However, be mindful of potential risks and leverage the safety resources provided by the maintainers to ensure responsible deployment.
Updated Invalid Date
🤔
Meta-Llama-3-8B-Instruct
1.5K
The Meta-Llama-3-8B-Instruct is a large language model developed and released by Meta. It is part of the Llama 3 family of models, which come in 8 billion and 70 billion parameter sizes, with both pretrained and instruction-tuned variants. The instruction-tuned Llama 3 models are optimized for dialogue use cases and outperform many open-source chat models on common industry benchmarks. Meta has taken care to optimize these models for helpfulness and safety. The Llama 3 models use an optimized transformer architecture and were trained on a mix of publicly available online data. The 8 billion parameter version uses a context length of 8k tokens and is capable of tasks like commonsense reasoning, world knowledge, reading comprehension, and math. Compared to the earlier Llama 2 models, the Llama 3 models have improved performance across a range of benchmarks. Model inputs and outputs Inputs Text input only Outputs Generates text and code Capabilities The Meta-Llama-3-8B-Instruct model is capable of a variety of natural language generation tasks, including dialogue, summarization, question answering, and code generation. It has shown strong performance on benchmarks evaluating commonsense reasoning, world knowledge, reading comprehension, and math. What can I use it for? The Meta-Llama-3-8B-Instruct model is intended for commercial and research use in English. The instruction-tuned variants are well-suited for assistant-like chat applications, while the pretrained models can be further fine-tuned for a range of text generation tasks. Developers should carefully review the Responsible Use Guide before deploying the model in production. Things to try Developers may want to experiment with fine-tuning the Meta-Llama-3-8B-Instruct model on domain-specific data to adapt it for specialized applications. The model's strong performance on benchmarks like commonsense reasoning and world knowledge also suggests it could be a valuable foundation for building knowledge-intensive applications.
Updated Invalid Date
🌀
Meta-Llama-3-70B-Instruct
783
The Meta-Llama-3-70B-Instruct is a large language model (LLM) developed and released by Meta. It is part of the Meta Llama 3 family of models, which includes both 8B and 70B parameter versions in pre-trained and instruction-tuned variants. The Llama 3 instruction-tuned models are optimized for dialogue use cases and outperform many available open-source chat models on common industry benchmarks. Meta took great care in developing these models to optimize for helpfulness and safety. The Meta-Llama-3-8B-Instruct is a smaller 8 billion parameter version of the instruction-tuned Llama 3 model, while the Llama-2-70b-chat-hf is a 70 billion parameter Llama 2 model tuned specifically for chatbot applications. Model inputs and outputs Inputs Text input only Outputs Generates text and code Capabilities The Meta-Llama-3-70B-Instruct model is a powerful generative text model capable of a wide range of natural language tasks. It can engage in helpful and safe dialogue, generate coherent and relevant text, and even produce code. The model's large size and instruction tuning allow it to outperform many open-source chat models on industry benchmarks. What can I use it for? The Meta-Llama-3-70B-Instruct model is well-suited for commercial and research use cases that require an advanced language model for tasks like chatbots, content generation, code generation, and more. Developers can fine-tune the model for specific applications or use the pre-trained version as-is. The model's capabilities make it a valuable tool for businesses looking to enhance their conversational AI offerings or automate content creation. Things to try One interesting aspect of the Meta-Llama-3-70B-Instruct model is its strong performance on both language understanding and generation tasks. Developers can experiment with using the model for a variety of natural language applications, from open-ended dialogue to more structured tasks like question answering or summarization. The model's large size and instruction tuning also make it well-suited for few-shot learning, where it can adapt quickly to new tasks with limited training data.
Updated Invalid Date
🗣️
Meta-Llama-3-8B
76
The Meta-Llama-3-8B is part of the Meta Llama 3 family of large language models (LLMs) developed and released by Meta. This collection of pretrained and instruction tuned generative text models comes in 8B and 70B parameter sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many available open source chat models on common industry benchmarks. Meta took great care to optimize helpfulness and safety when developing these models. The Meta-Llama-3-70B and Meta-Llama-3-8B-Instruct are other models in the Llama 3 family. The 70B parameter model provides higher performance than the 8B, while the 8B Instruct model is optimized for assistant-like chat. Model inputs and outputs Inputs The Meta-Llama-3-8B model takes text input only. Outputs The model generates text and code output. Capabilities The Meta-Llama-3-8B demonstrates strong performance on a variety of natural language processing benchmarks, including general knowledge, reading comprehension, and task-oriented dialogue. It excels at following instructions and engaging in open-ended conversations. What can I use it for? The Meta-Llama-3-8B is intended for commercial and research use in English. The instruction tuned version is well-suited for building assistant-like chat applications, while the pretrained model can be adapted for a range of natural language generation tasks. Developers can leverage the Llama Guard and other Purple Llama tools to enhance the safety and reliability of applications using this model. Things to try The clear strength of the Meta-Llama-3-8B model is its ability to engage in open-ended, task-oriented dialogue. Developers can leverage this by building conversational interfaces that leverage the model's instruction-following capabilities to complete a wide variety of tasks. Additionally, the model's strong grounding in general knowledge makes it well-suited for building information lookup tools and knowledge bases.
Updated Invalid Date