Text Classification
Transformers
Safetensors
qwen3
bango
system-one
non-autoregressive
calibrated-decisions
classification
decision-making
routing
scoring
guardrails
commercial-use
text-embeddings-inference
Instructions to use doggydon007/bango-600m-nar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use doggydon007/bango-600m-nar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="doggydon007/bango-600m-nar")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("doggydon007/bango-600m-nar") model = AutoModelForSequenceClassification.from_pretrained("doggydon007/bango-600m-nar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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