Text Classification
Transformers
lora
fine-tuning
adaptive
research
nested-lora
synaptic-plasticity
rank-adaptation
Instructions to use Simo76/Unified-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Simo76/Unified-LoRA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Simo76/Unified-LoRA")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Simo76/Unified-LoRA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update MRPC example notebook with new code cells
91d7191 -
Update mrpc_example.ipynb
2d544ad -
Remove unnecessary blank line in notebook
121e571 -
Update mrpc_example.ipynb
48f590e
-
Add Unified LoRA MRPC Benchmark Example Notebook
This notebook demonstrates Unified LoRA on the GLUE MRPC (paraphrase detection) task, including setup, data loading, and evaluation of both baseline and unified LoRA models.c567b69