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aneessaheba / peft-banking-classifier

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Fine-tunes Google FLAN-T5-base with LoRA (PEFT) on Banking77 to classify 77 banking intents. Trains only 1.77M params (0.71%) in ~2hrs on free Colab GPU. Served via FastAPI REST API with batch prediction, Docker support & evaluation metrics.

python docker machine-learning natural-language-processing deep-learning text-classification rest-api transformers pytorch seq2seq lora nlp-machine-learning intent-classification peft colab-notebook fastapi huggingface banking77 flan-t5 fine-tuning-llm
  • Updated Mar 3, 2026
  • Jupyter Notebook

danlex / nanolearn

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Frozen encoder + Mahalanobis prototype for class-incremental intent classification. 50+ experiments across BANKING77, CLINC150, HWU64, AG News. Matches fine-tuned baselines at 5MB state with zero forgetting, order-invariance, 455 QPS.

python nlp benchmark machine-learning research reproducible-research pytorch mahalanobis-distance intent-classification continual-learning catastrophic-forgetting few-shot-learning sentence-transformers clinc150 class-incremental-learning prototype-learning banking77 frozen-encoder
  • Updated Apr 13, 2026
  • Python

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