MaziyarPanahi/calme-2.5-qwen2-7b

Model Overview

MaziyarPanahi/calme-2.5-qwen2-7b is a 7.6 billion parameter language model developed by MaziyarPanahi. It is a fine-tuned iteration of the Qwen/Qwen2-7B base model, with the explicit goal of improving its performance across a range of benchmarks. This model supports a very large context window of 131,072 tokens, enabling it to process and generate long sequences of text.

Key Features

• Base Model: Fine-tuned from the robust Qwen/Qwen2-7B architecture.
• Parameter Count: Features 7.6 billion parameters, offering a balance between performance and computational efficiency.
• Extended Context Length: Boasts a significant 131,072 token context window, ideal for tasks requiring deep contextual understanding.
• Prompt Template: Utilizes the ChatML prompt format for structured conversational interactions.

Usage and Availability

This model is designed for general text generation tasks, leveraging its fine-tuned capabilities. Quantized GGUF versions are also available for optimized local deployment. Evaluation results on the Open LLM Leaderboard are anticipated to provide further insights into its performance characteristics.