andharsm/qwen25-7b-indonesian-sft-exp2
The andharsm/qwen25-7b-indonesian-sft-exp2 is a 7.6 billion parameter Qwen2.5-based language model, fine-tuned by andharsm. This model was specifically trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning from the unsloth/Qwen2.5-7B-Instruct-bnb-4bit base. Its primary differentiation lies in its optimized training process for efficiency, making it suitable for applications requiring a Qwen2.5 model with an efficient fine-tuning lineage.
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Model Overview
The andharsm/qwen25-7b-indonesian-sft-exp2 is a 7.6 billion parameter language model developed by andharsm. It is fine-tuned from the unsloth/Qwen2.5-7B-Instruct-bnb-4bit base model, leveraging the Unsloth library and Huggingface's TRL for an accelerated training process.
Key Characteristics
- Base Model: Qwen2.5-7B-Instruct architecture.
- Parameter Count: 7.6 billion parameters.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training speed compared to conventional methods.
- License: Released under the Apache-2.0 license.
Use Cases
This model is particularly well-suited for developers and researchers looking for a Qwen2.5-based model that benefits from an optimized and efficient fine-tuning process. It can be a strong candidate for applications where the underlying Qwen2.5 capabilities are desired, with an emphasis on the efficiency of its development and potential for further rapid iteration.