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") - Notebooks
- Google Colab
- Kaggle
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## Acknowledgements
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* Joe Davison and his article on [Zero-Shot Learning in Modern NLP](https://joeddav.github.io/blog/2020/05/29/ZSL.html)
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* Jeremy
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## Acknowledgements
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* Joe Davison and his article on [Zero-Shot Learning in Modern NLP](https://joeddav.github.io/blog/2020/05/29/ZSL.html)
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* Jeremy Howard, fast.ai and his notebook [Iterate like a grandmaster](https://www.kaggle.com/code/antoinemacia/iterate-like-a-grandmaster)
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