Instructions to use tartuNLP/mmBERT-small-m-edu-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tartuNLP/mmBERT-small-m-edu-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tartuNLP/mmBERT-small-m-edu-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tartuNLP/mmBERT-small-m-edu-classifier") model = AutoModelForSequenceClassification.from_pretrained("tartuNLP/mmBERT-small-m-edu-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a853bbedd87114c432148c2da564a082d68a009d47735e52b6dd803a310ec2de
- Size of remote file:
- 34.4 MB
- SHA256:
- 609d8f4c067cd3950f88594c5a802616cea245823836ef5848ee4fc40aab5b6f
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