Meta-Llama-3-8B-Instruct-GGUF
Maintainer: lmstudio-community
154
🤯
| 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-3-8B-Instruct is a community model created by the lmstudio-community based on Meta's open-sourced Meta-Llama-3-8B-Instruct model. This 8 billion parameter model is an instruction-tuned version of the Llama 3 language model, optimized for dialogue and outperforming many open-source chat models. The model was developed by Meta with a focus on helpfulness and safety.
Model Inputs and Outputs
Inputs
- Text prompts
Outputs
- Generated text responses
Capabilities
The Meta-Llama-3-8B-Instruct model excels at a variety of natural language tasks, including multi-turn conversations, general knowledge questions, and even coding. It is highly capable at following system prompts to produce the desired behavior.
What Can I Use It For?
The Meta-Llama-3-8B-Instruct model can be used for a wide range of applications, from building conversational AI assistants to generating content for creative projects. The model's instruction-following capabilities make it well-suited for use cases like customer support, virtual assistants, and even creative writing. Additionally, the model's strong performance on coding-related tasks suggests it could be useful for applications like code generation and programming assistance.
Things to Try
One interesting capability of the Meta-Llama-3-8B-Instruct model is its ability to adopt different personas and respond accordingly. By providing a system prompt that sets the model's role, such as "You are a pirate chatbot who always responds in pirate speak!", you can generate creative and engaging conversational outputs. Another interesting area to explore is the model's performance on complex reasoning and problem-solving tasks, where its strong knowledge base and instruction-following skills could prove valuable.
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-3-70B-Instruct-GGUF
94
The Meta-Llama-3-70B-Instruct-GGUF model is a large language model developed by the lmstudio-community team. It is a community model built on top of Meta's Meta-Llama-3-70B-Instruct base, with GGUF quantization provided by bartowski. This model represents a significant advancement in the Llama family, with performance reaching and often exceeding GPT-3.5 despite being an open-source model. The Meta-Llama-3-8B-Instruct-GGUF and Meta-Llama-3-70B models are similar but smaller and larger versions of the Llama 3 family, respectively. All of these models excel at general usage situations like multi-turn conversations, world knowledge, and coding tasks. Model inputs and outputs Inputs The model takes in text as its input. Outputs The model generates text and code as its outputs. Capabilities The Meta-Llama-3-70B-Instruct-GGUF model is very capable at following instructions provided in the system prompt. It can engage in creative conversations, demonstrate general knowledge, and complete coding tasks. Examples include: Creative conversations**: Using a system prompt to have the model roleplay as a pirate chatbot responding in pirate speak. General knowledge**: Answering questions about the world and demonstrating broad understanding. Coding**: Generating code to complete programming tasks. What can I use it for? The Meta-Llama-3-70B-Instruct-GGUF model can be used for a wide variety of natural language processing tasks, from chatbots and virtual assistants to content generation and code completion. The large 70B parameter size and instruction tuning make it a powerful tool for developers and researchers looking to push the boundaries of what's possible with large language models. Things to try One interesting aspect of this model is its ability to follow system prompts to tailor its behavior. Try giving it different persona-based prompts, like having it roleplay as a pirate, to see how it adapts its language and responses. You can also experiment with providing it with coding tasks or open-ended questions to gauge the depth of its knowledge and capabilities.
Updated Invalid Date
👀
Meta-Llama-3.1-8B-Instruct-GGUF
177
The Meta-Llama-3.1-8B-Instruct-GGUF is an updated version of the Llama 3 model family created by Meta. It builds upon the previous Llama 3 models with improved performance, especially in multilingual tasks. This model is considered state-of-the-art for open-source language models and can be used for a wide variety of text-to-text tasks. Model inputs and outputs The Meta-Llama-3.1-8B-Instruct-GGUF model takes text prompts as input and generates corresponding text outputs. The prompts can be formatted using the 'Llama 3' preset in the LM Studio interface, which includes a header system to specify the role of the different parts of the prompt. Inputs System prompt**: Provides context and instructions for the model User prompt**: The actual text that the model will generate a response to Outputs Assistant response**: The text generated by the model based on the provided prompts Capabilities The Meta-Llama-3.1-8B-Instruct-GGUF model is highly capable and can be used for a wide variety of text generation tasks, such as answering questions, summarizing text, and generating creative content. It has been trained on a large corpus of data, including 25 million synthetically generated samples, which gives it broad knowledge and strong language understanding abilities. What can I use it for? The Meta-Llama-3.1-8B-Instruct-GGUF model can be used for a wide range of applications, from chatbots and virtual assistants to content creation and text summarization. Its capabilities make it a versatile tool that can be integrated into various projects and business scenarios. For example, you could use it to generate product descriptions, write blog posts, or create customer support chatbots. Things to try One interesting thing to try with the Meta-Llama-3.1-8B-Instruct-GGUF model is to experiment with different prompts and see how it responds. The model's broad knowledge and language understanding capabilities allow it to handle a wide range of topics and tasks, so it's worth exploring its limits and discovering new ways to leverage its capabilities.
Updated Invalid Date
🌐
Meta-Llama-3-120B-Instruct-GGUF
46
Meta-Llama-3-120B-Instruct is a large language model created by the LM Studio community. It is a meta-model based on the Meta-Llama-3-70B-Instruct model, with expanded capabilities through self-merging. This model was inspired by other large-scale models like Goliath-120B, Venus-120B-v1.0, and MegaDolphin-120B. Model inputs and outputs Meta-Llama-3-120B-Instruct is a text-to-text model that takes in a prompt formatted with a system prompt, user input, and a placeholder for the assistant's response. The model's outputs are continuations of the provided prompt, generating coherent and contextual text. Inputs System prompt**: A prompt that sets the tone and context for the model's response User input**: The text that the user provides for the model to continue or respond to Outputs Assistant response**: The model's generated continuation of the provided prompt, adhering to the system prompt's instructions Capabilities Meta-Llama-3-120B-Instruct excels at creative writing tasks, showcasing a strong writing style and interesting, albeit sometimes unhinged, outputs. However, the model may struggle in more formal or analytical tasks compared to larger language models like GPT-4. What can I use it for? This model is well-suited for creative writing projects, such as short stories, poetry, or worldbuilding. The model's unique perspective and voice can add an interesting flair to your writing. While the model may not be the most reliable for tasks requiring factual accuracy or logical reasoning, it can be a valuable tool for sparking inspiration and exploring new creative directions. Things to try Try providing the model with a range of prompts, from simple story starters to more complex worldbuilding exercises. Observe how the model's responses evolve and the unique perspectives it brings to the table. Experiment with adjusting the temperature and other generation parameters to find the sweet spot for your desired style and content.
Updated Invalid Date
📊
Meta-Llama-3-70B-Instruct-GGUF
45
The Meta-Llama-3-70B-Instruct-GGUF is a large language model developed by Meta. It is a quantized and compressed version of the original Meta-Llama-3-70B-Instruct model, created using the llama.cpp library for improved inference efficiency. The Llama 3 model family consists of both 8B and 70B parameter versions, with both pretrained and instruction-tuned variants. The instruction-tuned models like Meta-Llama-3-70B-Instruct-GGUF are optimized for dialogue and chat use cases, and outperform many open-source chat models on industry benchmarks. Meta has also released smaller 8B versions of the Llama 3 model. Model inputs and outputs Inputs Text**: The model accepts text as its input. Outputs Text and code**: The model generates text and code as output. Capabilities The Meta-Llama-3-70B-Instruct-GGUF model is a powerful natural language generation tool capable of a wide variety of tasks. It can engage in conversational dialogue, answer questions, summarize information, and even generate creative content like stories and poems. The model has also demonstrated strong performance on benchmarks testing its reasoning and analytical capabilities. What can I use it for? The Meta-Llama-3-70B-Instruct-GGUF model is well-suited for commercial and research applications that involve natural language processing and generation. Some potential use cases include: Developing intelligent chatbots and virtual assistants Automating report writing and content generation Enhancing search and recommendation systems Powering creative writing tools Enabling more natural human-AI interactions Things to try One interesting aspect of the Meta-Llama-3-70B-Instruct-GGUF model is its ability to engage in open-ended dialogue while maintaining a high degree of safety and helpfulness. Developers can experiment with prompts that test the model's conversational capabilities, such as role-playing different personas or exploring hypothetical scenarios. Additionally, the model's strong performance on reasoning tasks suggests it could be useful for building applications that require analytical or problem-solving abilities.
Updated Invalid Date