Instructions to use microsoft/deberta-xlarge-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/deberta-xlarge-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="microsoft/deberta-xlarge-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("microsoft/deberta-xlarge-mnli") model = AutoModelForSequenceClassification.from_pretrained("microsoft/deberta-xlarge-mnli") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#10 opened about 1 year ago
by
SFconvertbot
Adding `safetensors` variant of this model
#9 opened about 1 year ago
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SFconvertbot
Adding `safetensors` variant of this model
#8 opened over 1 year ago
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SFconvertbot
Adding `safetensors` variant of this model
#7 opened over 1 year ago
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SFconvertbot
Adding `safetensors` variant of this model
#6 opened over 1 year ago
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SFconvertbot
Updates incorrect tokenizer configuration file
#5 opened over 2 years ago
by
lysandre
Adding `safetensors` variant of this model
#2 opened about 3 years ago
by
SFconvertbot