yeonghwan123/Llama3-alpaca-tuned-and-merged
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kPublished:Feb 12, 2026Architecture:Transformer Cold
The yeonghwan123/Llama3-alpaca-tuned-and-merged model is an 8 billion parameter language model, fine-tuned from the Llama 3 architecture. This model has been instruction-tuned using an Alpaca dataset, enhancing its ability to follow instructions and perform general-purpose conversational tasks. With a context length of 8192 tokens, it is designed for versatile applications requiring robust instruction-following capabilities.
Loading preview...
yeonghwan123/Llama3-alpaca-tuned-and-merged: An Instruction-Tuned Llama 3 Model
This model is an 8 billion parameter language model based on the Llama 3 architecture, developed by yeonghwan123. It has undergone instruction-tuning using an Alpaca dataset, which significantly improves its ability to understand and execute user instructions.
Key Capabilities
- Instruction Following: Enhanced through Alpaca fine-tuning, making it proficient in responding to a wide range of prompts and commands.
- General-Purpose Language Generation: Capable of generating coherent and contextually relevant text for various tasks.
- Context Handling: Supports a context length of 8192 tokens, allowing for processing and generating longer sequences of text.
Good For
- Conversational AI: Suitable for chatbots and virtual assistants that require strong instruction adherence.
- Text Generation: Ideal for tasks like content creation, summarization, and question answering where precise instruction following is crucial.
- Prototyping and Development: A solid base model for further fine-tuning on specific downstream applications requiring an instruction-tuned foundation.