Model Overview

The izaanz/Thesis_RTX5090_SFT_Merged is a 7.6 billion parameter language model, fine-tuned by izaanz from the unsloth/qwen2.5-coder-7b-instruct base model. It leverages the Qwen2.5 architecture and is designed for instruction-following tasks.

Key Capabilities

• Efficient Training: This model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
• Large Context Window: It supports a substantial context length of 131072 tokens, enabling it to process and generate responses based on extensive input.
• Instruction Following: As an instruction-tuned model, it is capable of understanding and executing a wide range of user instructions.

Good For

• Applications requiring a model with a large context window.
• Tasks benefiting from an instruction-tuned Qwen2.5-based model.
• Scenarios where efficient training methodologies are a key consideration.