Instructions to use mjwong/e5-large-v2-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mjwong/e5-large-v2-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="mjwong/e5-large-v2-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mjwong/e5-large-v2-mnli") model = AutoModelForSequenceClassification.from_pretrained("mjwong/e5-large-v2-mnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ae3334ce750060e64c621c09fa8e024add3bd915024c5b817b3920d8892397a
- Size of remote file:
- 1.34 GB
- SHA256:
- ec4e33c1ffc14c59edd7dc3eb70df58890a8b51b2c005d0b5efe4ff30cd4ee9b
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