Model Fine-Tuning (LoRA)
by AaaS · open-source · Last verified 2026-03-01
Fine-tunes language models using Low-Rank Adaptation (LoRA) for parameter-efficient training. Handles dataset preparation, adapter configuration, training loop with gradient accumulation, evaluation, and adapter merging for deployment-ready models.
https://aaas.blog/script/model-fine-tuning-lora ↗B
B—Above Average
Adoption: B+Quality: AFreshness: ACitations: BEngagement: F
Specifications
- License
- MIT
- Pricing
- open-source
- Capabilities
- lora-training, dataset-preparation, adapter-configuration, evaluation, adapter-merging
- Integrations
- transformers, peft, datasets, wandb, bitsandbytes
- Use Cases
- domain-adaptation, task-specialization, style-training, instruction-tuning
- API Available
- No
- Language
- python
- Dependencies
- transformers, peft, datasets, wandb, bitsandbytes, accelerate
- Environment
- Python 3.11+ with CUDA 12 and 24GB+ VRAM
- Est. Runtime
- 30-180 minutes depending on model size and dataset
- Tags
- script, automation, fine-tuning, lora, training
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
62.6Adoption
72
Quality
84
Freshness
82
Citations
68
Engagement
0