Text Classification
Transformers
PyTorch
English
distilbert
customer-service-tickets
github-issues
bart-large-mnli
zero-shot-classification
NLP
text-embeddings-inference
Instructions to use AntoineMC/distilbart-mnli-github-issues with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AntoineMC/distilbart-mnli-github-issues with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AntoineMC/distilbart-mnli-github-issues")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AntoineMC/distilbart-mnli-github-issues") model = AutoModelForSequenceClassification.from_pretrained("AntoineMC/distilbart-mnli-github-issues", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00a8c29e2dcd174f9fb380dd1451d9f5b8e4fa468ffb738e3007f31eacde6c9e
- Size of remote file:
- 3.02 kB
- SHA256:
- 39f13e65390f3752e15021ee56c1c6c3bb1fe72d9ecbce77c3729287bcf1f05d
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