MaziyarPanahi/calme-2.6-qwen2-7b
MaziyarPanahi/calme-2.6-qwen2-7b is a 7.6 billion parameter causal language model fine-tuned by MaziyarPanahi from the Qwen/Qwen2-7B architecture. This model aims to improve upon the base Qwen2-7B model across various benchmarks. It is designed for general text generation tasks, leveraging its fine-tuned capabilities to enhance performance.
Loading preview...
Model Overview
MaziyarPanahi/calme-2.6-qwen2-7b is a fine-tuned version of the Qwen/Qwen2-7B model, developed by MaziyarPanahi. This 7.6 billion parameter model is designed to enhance the performance of the base Qwen2-7B architecture across various benchmarks. It supports a substantial context length of 131,072 tokens, making it suitable for processing extensive inputs and generating detailed responses.
Key Capabilities
- Improved Performance: Aims to offer enhanced capabilities over the foundational Qwen2-7B model through fine-tuning.
- Large Context Window: Features a 131,072-token context length, allowing for deep understanding and generation based on large amounts of information.
- ChatML Prompt Template: Utilizes the
ChatMLformat for structured conversational interactions, ensuring consistent input and output formatting.
Good For
- General Text Generation: Suitable for a wide range of applications requiring coherent and contextually relevant text output.
- Conversational AI: Its adherence to the ChatML prompt template makes it well-suited for chatbot development and interactive AI systems.
- Applications requiring large context: Ideal for tasks where processing and generating text based on extensive prior information is crucial.