danieltorscho/kyr-qw25-7b-instruct-gen110
The danieltorscho/kyr-qw25-7b-instruct-gen110 is a 7.6 billion parameter instruction-tuned causal language model developed by danieltorscho. This model is a fine-tuned variant of Qwen2.5-7B-Instruct, optimized for performance and efficiency. It was trained using Unsloth and Huggingface's TRL library, enabling faster training. With a 32768 token context length, it is suitable for tasks requiring extensive contextual understanding.
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Model Overview
The danieltorscho/kyr-qw25-7b-instruct-gen110 is a 7.6 billion parameter instruction-tuned language model, developed by danieltorscho. It is based on the Qwen2.5-7B-Instruct architecture and has been fine-tuned for enhanced performance.
Key Characteristics
- Architecture: Fine-tuned from
unsloth/Qwen2.5-7B-Instruct-bnb-4bit. - Training Efficiency: This model was trained with a focus on speed, utilizing Unsloth and Huggingface's TRL library, resulting in 2x faster training compared to standard methods.
- Context Length: Supports a substantial context window of 32768 tokens, allowing for processing and understanding of longer inputs.
- License: Distributed under the Apache-2.0 license.
Use Cases
This model is well-suited for applications requiring an instruction-following language model that benefits from efficient training methodologies. Its large context window makes it particularly effective for tasks involving detailed instructions, summarization of lengthy documents, or complex conversational agents where retaining extensive conversational history is crucial.