Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v3
deberta-v2`
deberta-mnli
Instructions to use NDugar/v3large-2epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NDugar/v3large-2epoch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="NDugar/v3large-2epoch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NDugar/v3large-2epoch") model = AutoModelForSequenceClassification.from_pretrained("NDugar/v3large-2epoch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scaler.pt from NDugar/v3large-2epoch: direct link, hf CLI and curl.
- Browser
- Download file 559 Bytes
-
https://huggingface.co/NDugar/v3large-2epoch/resolve/main/scaler.pt
- Command line
-
hf download hf://NDugar/v3large-2epoch/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/NDugar/v3large-2epoch/resolve/main/scaler.pt
559 Bytes
- Xet hash:
- c89a5113eef82f35f82bfa6b4781f207cb0a834f29de15ab901540d81af63b5e
- Size of remote file:
- 559 Bytes
- SHA256:
- ab36ce7a7e61de87c96c6d3732c90fce495da98b591a86590de7ef9a044e40ce
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