๐ต Qwen3-4B-Lyrics-GGUF ๐ต
โจ Model Description
This repository contains specialized GGUF versions of the Qwen3-4B model fine-tuned to create exceptional song lyrics. Each model has been carefully trained on a curated dataset of high-quality lyrics, enhancing its reasoning capabilities and creative expression.
๐ฆ Available Models
๐ฎ Model File | ๐ง Base Model | โ๏ธ Quantization | ๐ Size | ๐ Optimization |
---|---|---|---|---|
qwen3-4bf16.gguf |
Qwen3-4B | F16 | 4B parameters | Standard precision |
qwen3-4b-230-f16.gguf |
Qwen3-4B | F16 | 4B parameters | 230 training steps |
๐งช Training Details
๐ Aspect | ๐ Details |
---|---|
Dataset | ๐ฏ High-quality reasoning lyrics dataset (private) |
Examples | ๐ 661 unique examples per model |
Training Strategy | ๐ Individual fine-tuning for each model variant |
Evaluation Metrics | ๐ Loss, Learning Rate, Gradient Norm, Steps/Samples per Second |
๐ Performance Metrics
โจ qwen3-4b-230-f16.gguf
Metric | Final Value |
---|---|
๐ Training Loss | 0.2627 |
๐ Evaluation Loss | 2.0974 |
๐ Learning Rate | 0.00018248 |
๐ Gradient Norm | 0.71101 |
โฑ๏ธ Steps per Second | 1.835 |
๐ Samples per Second | 10.554 |
๐ Epochs | 8.87662 |
โจ qwen3-4bf16.gguf
Metric | Final Value |
---|---|
๐ Training Loss | 1.0589 |
๐ Evaluation Loss | 1.48644 |
๐ Learning Rate | 4.3798e-8 |
๐ Gradient Norm | 0.44541 |
โฑ๏ธ Steps per Second | 2.725 |
๐ Samples per Second | 10.445 |
๐ Epochs | 2.99781 |
๐ How to Use
Simple Setup
- ๐ฅ Download LM Studio for an easy graphical interface
- โฌ๏ธ Download the model from this repository
- ๐ Load the model in LM Studio and start generating lyrics!
Advanced Usage
- ๐ง For command-line enthusiasts, use llama.cpp
- ๐ป Download the model and run it locally for maximum control
๐ Acknowledgements
This project would not have been possible without the following resources:
- Base Model: Qwen/Qwen3-4B - The original foundation model developed by the Qwen team at Alibaba Cloud
- Training Framework: Axolotl - An efficient and user-friendly fine-tuning framework that made the training process possible
We extend our sincere gratitude to these teams for their outstanding work and contributions to the open-source AI community.
๐ค Create songs that inspire, lyrics that move, and words that resonate ๐ค
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