Instructions to use s-nlp/E5-EverGreen-Multilingual-Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use s-nlp/E5-EverGreen-Multilingual-Small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="s-nlp/E5-EverGreen-Multilingual-Small")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("s-nlp/E5-EverGreen-Multilingual-Small") model = AutoModelForSequenceClassification.from_pretrained("s-nlp/E5-EverGreen-Multilingual-Small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e97e22ce09f70026280b7b4dd2e87e72f39d17b377be0d1959dade243f3fe8fa
- Size of remote file:
- 17.1 MB
- SHA256:
- cd98e5698b201ba914efb8c18b6709fa8735ab71dcad8d2b431e52e8bf68d932
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