Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use pepa/deberta-v3-large-fever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pepa/deberta-v3-large-fever with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pepa/deberta-v3-large-fever")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pepa/deberta-v3-large-fever") model = AutoModelForSequenceClassification.from_pretrained("pepa/deberta-v3-large-fever", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from pepa/deberta-v3-large-fever: direct link, hf CLI and curl.
- Browser
- Download file 1.74 GB
-
https://huggingface.co/pepa/deberta-v3-large-fever/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://pepa/deberta-v3-large-fever/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pepa/deberta-v3-large-fever/resolve/main/pytorch_model.bin
1.74 GB
- Xet hash:
- e9b13365ecaf622bcc29f7953d744bce343ef787ab9d1da39e4a329a639372f9
- Size of remote file:
- 1.74 GB
- SHA256:
- d69f702bce4689cbb64891e8f8fb258a1d8737ab3b06869323b29c35e2a7bbc1
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