What it is
The de-facto hub for transformer models. Load BERT, T5, Llama, Mistral, Whisper or any of 200k community models with three lines of Python — then fine-tune them on your data with Trainer or accelerate.
How Vaaani uses it
- Fine-tuning a domain-specific BERT for classification or NER
- Running inference on Llama / Mistral with quantization for cheap GPUs
- Distilling large models down to fast student models for production
- Sharing internal model weights privately via the Hub
Why it makes the cut
Hugging Face removes 90% of the boilerplate around modern NLP. Every Vaaani build that needs a custom model starts here.
Sample code
from transformers import pipeline clf = pipeline("text-classification", model="vaaani/support-intent-bert") clf("My order hasn't arrived yet") # [{'label': 'shipping_issue', 'score': 0.97}]
Related in the Vaaani stack
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