Danleon56/qwen2.5-7b-chioma-sft-merged
The Danleon56/qwen2.5-7b-chioma-sft-merged model is a 7.6 billion parameter Qwen2.5-based language model, fine-tuned by Danleon56. This model was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. It is designed for general language generation tasks, leveraging the Qwen2.5 architecture for broad applicability.
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Model Overview
Danleon56/qwen2.5-7b-chioma-sft-merged is a 7.6 billion parameter language model, fine-tuned by Danleon56. It is based on the Qwen2.5 architecture, specifically fine-tuned from unsloth/Qwen2.5-7B-Instruct-bnb-4bit.
Key Characteristics
- Architecture: Qwen2.5-based, a causal language model known for its general-purpose capabilities.
- Parameter Count: 7.6 billion parameters, offering a balance between performance and computational efficiency.
- Training Method: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitates faster training processes.
- License: Distributed under the Apache-2.0 license, allowing for broad use and modification.
Intended Use Cases
This model is suitable for a variety of natural language processing tasks where a Qwen2.5-based model with efficient fine-tuning is beneficial. Its general-purpose nature makes it adaptable for applications such as:
- Text generation and completion.
- Instruction following (given its base model).
- General conversational AI.
- Prototyping and development where rapid iteration is key due to the Unsloth-enabled training.