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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#3)
- Adding `safetensors` variant of this model (ab6d5e4057481583df31a2abba35e78e027dd838) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>cfa538a
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Model Card (#2)
hhschu +1: Ezi - Model Card (c213a4b99cbb618477949c1483b6916d023c2e45) Co-authored-by: Ezi Ozoani <Ezi@users.noreply.huggingface.co>996dacf
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Add TF weights (#1)
hhschu +1: joaogante - Add TF weights (20fae5e389891a08e888e902758ed97384cdf1b7) Co-authored-by: Joao Gante <joaogante@users.noreply.huggingface.co>9487bd4
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add model
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