Zero-Shot Classification
Transformers
PyTorch
TensorFlow
Safetensors
English
distilbert
text-classification
Instructions to use typeform/distilbert-base-uncased-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use typeform/distilbert-base-uncased-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="typeform/distilbert-base-uncased-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("typeform/distilbert-base-uncased-mnli") model = AutoModelForSequenceClassification.from_pretrained("typeform/distilbert-base-uncased-mnli") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ee2e5133f5320a060eb5a0e7369a20489624c2d9454c25ee59a591ce17b8947
- Size of remote file:
- 268 MB
- SHA256:
- e9c34cf80a78f251571afee70b7139ce1c5137a4c35a5a984ae519337e2092d0
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