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:
- a162f5c13c1dcf30b3283a67f809802b1f69ea0e2f2e59b0ba046f1da4626a97
- Size of remote file:
- 599 MB
- SHA256:
- 63982dc593fd03792177df26d7f15c9db5c41062da2f88325e63935638ab1a20
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