madiwarPtasanna/qwen_finetune_16bit
TEXT GENERATIONConcurrency Cost:1Model Size:0.8BQuant:BF16Ctx Length:32kPublished:Mar 6, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The madiwarPtasanna/qwen_finetune_16bit model is a 0.8 billion parameter Qwen3-based causal language model, developed by madiwarPtasanna. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is optimized for tasks benefiting from efficient fine-tuning on a compact Qwen3 architecture.
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Model Overview
The madiwarPtasanna/qwen_finetune_16bit is a 0.8 billion parameter language model based on the Qwen3 architecture. It was developed by madiwarPtasanna and fine-tuned from the unsloth/Qwen3-0.6B-Base model.
Key Characteristics
- Efficient Fine-tuning: This model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- Base Model: It leverages the Qwen3 architecture, known for its performance in a compact size.
- License: The model is released under the Apache-2.0 license.
Potential Use Cases
This model is suitable for developers looking for:
- Rapid Prototyping: Its efficient fine-tuning process makes it ideal for quick experimentation and iteration on specific tasks.
- Resource-Constrained Environments: The 0.8 billion parameter size allows for deployment in environments with limited computational resources.
- Custom Applications: Users can further fine-tune this model for specialized downstream applications where a compact and efficiently trained Qwen3 variant is beneficial.