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")# 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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2a22a45dd2e9db9f69a0db295c48712eb58c185b92138b2978d8e7222902a7f
- Size of remote file:
- 3.96 kB
- SHA256:
- a69a93fd6f6ff40d061d2890cc2c653840203973675b926ca88eacda8a741022
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