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---
tags:
- llama
- alpaca
- qlora
- unsloth
- instruction-tuning
- fine-tuned
base_model: unsloth/llama-3.1-8b-bnb-4bit
library_name: peft
license: apache-2.0
datasets:
- tatsu-lab/alpaca
language:
- en
pipeline_tag: text-generation
---
# unsloth/mistral-7b-v0.3-bnb-4bit Fine-tuned with QLoRA (Unsloth) on Alpaca
This model is a fine-tuned version of [`unsloth/mistral-7b-v0.3-bnb-4bit`](https://huggingface.co/unsloth/mistral-7b-v0.3-bnb-4bit) using **QLoRA** and [Unsloth](https://github.com/unslothai/unsloth) for efficient instruction-tuning.
## 📖 Training Details
- **Dataset**: [`yahma/alpaca-cleaned`](https://huggingface.co/datasets/yahma/alpaca-cleaned)
- **QLoRA**: 4 bit quantization (NF4) using `bitsandbytes`
- **LoRA Rank**: 16 (adjust based on your config)
- **LoRA Alpha**: 16
- **Batch Size**: 2 per device
- **Gradient Accumulation**: 4
- **Learning Rate**: 2e-4
- **Epochs**: 1
- **Trainer**: `trl.SFTTrainer`
## 💡 Notes
- Optimized for memory-efficient fine-tuning with Unsloth
- No evaluation was run during training — please evaluate separately
## 📝 License
Apache 2.0 |