AI-Sweden-Models/Llama-3-8B-instruct
AI-Sweden-Models/Llama-3-8B-instruct is an 8 billion parameter instruction-tuned causal language model developed by AI-Sweden-Models, based on the Llama 3 architecture. Trained on the LUMI supercomputer, this model is designed for general-purpose conversational AI and instruction following, demonstrating capabilities in tasks like multi-turn dialogue and basic arithmetic. It leverages an 8192-token context length for processing longer prompts and generating coherent responses.
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AI-Sweden-Models/Llama-3-8B-instruct Overview
AI-Sweden-Models/Llama-3-8B-instruct is an 8 billion parameter instruction-tuned language model developed by AI-Sweden-Models. It is built upon the base model AI-Sweden-Models/Llama-3-8B and has been specifically fine-tuned to follow instructions and engage in conversational tasks.
Key Capabilities
- Instruction Following: Designed to accurately interpret and execute user instructions.
- Conversational AI: Capable of engaging in multi-turn dialogues, as demonstrated by its ability to answer questions and provide detailed explanations.
- Multilingual Interaction: The provided example showcases its ability to process and respond to prompts in Swedish, indicating potential for multilingual applications.
- Arithmetic: Can perform basic mathematical operations within a conversational context.
- Context Length: Utilizes an 8192-token context window, allowing for more extensive input and output generation.
Training Details
The model's instruction tuning was performed on the LUMI supercomputer as part of the DeployAI EU project. This advanced computational resource facilitated the fine-tuning process, enhancing its instruction-following capabilities.
Good For
- Developing chatbots and virtual assistants that require robust instruction adherence.
- Applications needing detailed, conversational responses to user queries.
- Tasks involving basic reasoning and information retrieval in a dialogue format.
- Use cases where a balance between model size and performance for instruction-tuned tasks is desired.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.