Zero-Shot Classification
Transformers
PyTorch
English
deberta-v2
text-classification
deberta-v3
deberta-v2`
deberta-mnli
Instructions to use NDugar/1epochv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NDugar/1epochv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="NDugar/1epochv3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NDugar/1epochv3") model = AutoModelForSequenceClassification.from_pretrained("NDugar/1epochv3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scaler.pt from NDugar/1epochv3: direct link, hf CLI and curl.
- Browser
- Download file 559 Bytes
-
https://huggingface.co/NDugar/1epochv3/resolve/main/scaler.pt
- Command line
-
hf download hf://NDugar/1epochv3/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/NDugar/1epochv3/resolve/main/scaler.pt
559 Bytes
- Xet hash:
- 26ec311c6092b9e4bd2dcf56b2a9aa9ddcc2d072104fa711fac78930a4253a2a
- Size of remote file:
- 559 Bytes
- SHA256:
- 567c10a1280c48158a89d082c46d35fc3dbbc139dfd27a00121abd70b5d798fc
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