Instructions to use mjwong/e5-large-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mjwong/e5-large-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="mjwong/e5-large-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mjwong/e5-large-mnli") model = AutoModelForSequenceClassification.from_pretrained("mjwong/e5-large-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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README.md
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datasets:
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model-index:
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- name: e5-large-mnli
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results: []
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pipeline_tag: zero-shot-classification
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language:
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license: mit
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# e5-large-mnli
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language:
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license: mit
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datasets:
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- glue
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pipeline_tag: zero-shot-classification
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base_model: intfloat/e5-large
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model-index:
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- name: e5-large-mnli
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results: []
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---
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# e5-large-mnli
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