Model Overview

The gjyotin305/Qwen2.5-7B-Instruct_old_sft_alpaca_009 is a 7.6 billion parameter instruction-tuned language model. It was developed by gjyotin305 and finetuned from the unsloth/Qwen2.5-7B-Instruct base model.

Key Characteristics

• Architecture: Based on the Qwen2.5-7B-Instruct family.
• Parameter Count: 7.6 billion parameters.
• Context Length: Features a significant context window of 131,072 tokens, suitable for processing extensive inputs.
• Training Efficiency: This model was finetuned with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
• License: Distributed under the Apache-2.0 license.

Good For

• Instruction Following: Designed for tasks requiring precise adherence to instructions due to its instruction-tuned nature.
• Long Context Applications: Its large context window makes it well-suited for applications involving lengthy documents, code, or conversations.
• Efficient Deployment: As a model finetuned with Unsloth, it may offer advantages in terms of training speed and potentially optimized inference.