Instructions to use Cheng98/opt-350m-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheng98/opt-350m-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheng98/opt-350m-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheng98/opt-350m-mnli") model = AutoModelForSequenceClassification.from_pretrained("Cheng98/opt-350m-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4f23735bb8d019f6dd94ecb3096abea9b1678ba913ab3fc12838e82fb4e1c23
- Size of remote file:
- 1.32 GB
- SHA256:
- 7fc47afc14553377c0affbb13a83796c18c23561bd923f160f5b9fc7fc843044
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