Text Classification
Transformers
ONNX
Safetensors
English
modernbert
rag
governance
hallucination-detection
classification
fitz-gov
pyrrho
text-embeddings-inference
Instructions to use yafitzdev/pyrrho-v1-nano-g2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yafitzdev/pyrrho-v1-nano-g2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yafitzdev/pyrrho-v1-nano-g2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yafitzdev/pyrrho-v1-nano-g2") model = AutoModelForSequenceClassification.from_pretrained("yafitzdev/pyrrho-v1-nano-g2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.onnx.data from yafitzdev/pyrrho-v1-nano-g2: direct link, hf CLI and curl.
- Browser
- Download file 598 MB
-
https://huggingface.co/yafitzdev/pyrrho-v1-nano-g2/resolve/main/model.onnx.data
- Command line
-
hf download hf://yafitzdev/pyrrho-v1-nano-g2/model.onnx.data
-
curl -L -o model.onnx.data https://huggingface.co/yafitzdev/pyrrho-v1-nano-g2/resolve/main/model.onnx.data
598 MB
- Xet hash:
- cc51a37b1a1c545a7b3df342c6fa36fafe0224c2edb6c30bc7e8f1357fe6d752
- Size of remote file:
- 598 MB
- SHA256:
- 8e36e0b27d520b66e859813a93686e1cc414d3127df79a24a1fe36ccb3d8353e
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