Text Classification
Transformers
PyTorch
Safetensors
English
German
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use deepset/deberta-v3-base-injection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/deberta-v3-base-injection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deepset/deberta-v3-base-injection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("deepset/deberta-v3-base-injection") model = AutoModelForSequenceClassification.from_pretrained("deepset/deberta-v3-base-injection", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepset/deberta-v3-base-injection: direct link, hf CLI and curl.
- Browser
- Download file 738 MB
-
https://huggingface.co/deepset/deberta-v3-base-injection/resolve/refs%2Fpr%2F9/pytorch_model.bin
- Command line
-
hf download hf://deepset/deberta-v3-base-injection@refs/pr/9/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/deberta-v3-base-injection/resolve/refs%2Fpr%2F9/pytorch_model.bin
738 MB
- Xet hash:
- b0582be818fc3f31bc09107b9422a4dc6c01bec9b8af203b0e25a5514fd0f5c5
- Size of remote file:
- 738 MB
- SHA256:
- b086e0339311b8cbee4d0e8ec59a6355c85a60dee1d5bcb498c87ecc0427a7c9
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