Overview

Yaseal/llama3_3b_instruct_vallina_full_sft_30k is a 3.2 billion parameter instruction-tuned model, derived from the LLM-Research/Llama-3.2-3B-Instruct base. Its primary distinction lies in its fine-tuning on the deepmath_plain_30k_train dataset, indicating a specialized focus on mathematical and logical reasoning tasks. The model supports a substantial context length of 32768 tokens, allowing it to handle complex and lengthy problem descriptions or data inputs.

Key Capabilities

• Specialized Mathematical Reasoning: Fine-tuned on a deepmath dataset, suggesting enhanced performance in mathematical problem-solving and related logical tasks.
• Extended Context Window: With a 32768-token context length, it can process extensive prompts and maintain coherence over long interactions.
• Instruction Following: As an instruction-tuned model, it is designed to respond effectively to user commands and queries.

Good for

• Applications requiring robust mathematical understanding and problem-solving.
• Tasks involving long-form logical reasoning or code analysis where context is critical.
• Developing specialized agents or tools for scientific and engineering domains.