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")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Simo76/Unified-LoRA", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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--ub.com/Sva76/Unified-LoRa/blob/main/notebooks/unified_lora_demo.ipynb
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---
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library_name: transformers
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tags:
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- lora
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- fine-tuning
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- peft
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- adaptive
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- research
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datasets:
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- glue
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metrics:
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- accuracy
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- f1
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---
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# Unified-LoRA
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Adaptive LoRA fine-tuning with dynamic rank control.
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👉 Demo: https://github.com/Sva76/Unified-LoRa/blob/main/notebooks/unified_lora_demo.ipynb
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