Instructions to use CeroShrijver/m3e-base-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CeroShrijver/m3e-base-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CeroShrijver/m3e-base-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CeroShrijver/m3e-base-text-classification") model = AutoModelForSequenceClassification.from_pretrained("CeroShrijver/m3e-base-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 035211455398e7a5ac44c79faae03586f34c0c796e3c74ec47b120d25168bffd
- Size of remote file:
- 409 MB
- SHA256:
- 21347efb15ca78d04c4f0d2cb6f2874b983b1273edb971536925369093dd3192
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