Text Classification
Transformers
ONNX
Safetensors
English
modernbert
rag
governance
hallucination-detection
evidence-verification
pyrrho
fitz-gov-v2
multi-label-classification
text-embeddings-inference
Instructions to use yafitzdev/pyrrho-v2-nano-g1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yafitzdev/pyrrho-v2-nano-g1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yafitzdev/pyrrho-v2-nano-g1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yafitzdev/pyrrho-v2-nano-g1") model = AutoModelForSequenceClassification.from_pretrained("yafitzdev/pyrrho-v2-nano-g1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c3a6060010e9f4dc173a80025a6926b09520de555a11c01d34a0f8db4ce039b
- Size of remote file:
- 151 MB
- SHA256:
- 9c2db516e0babcefed860082ca3c2d94b2467d5554356dd24d9dbd00cb155ce6
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