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:
- e303d0d3e9d88b0c554b2629a8493b1537d5d72761d5c7e283464144055cf270
- Size of remote file:
- 3.96 kB
- SHA256:
- a9508f96bc81e7e124e0c1d6b02bd79a7a2bfc941a52125c2e8409d50c403a6f
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