Text Classification
Transformers
Safetensors
English
deberta-v2
cefr
vocabulary
english-learning
education
deberta-v3
word-level-classification
text-embeddings-inference
Instructions to use star092304/cefr-level-deberta-v3-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use star092304/cefr-level-deberta-v3-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="star092304/cefr-level-deberta-v3-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("star092304/cefr-level-deberta-v3-base") model = AutoModelForSequenceClassification.from_pretrained("star092304/cefr-level-deberta-v3-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab5da6c224a708ed55f1918b49bab99db29d5233d5c17b386052d731ffb82b80
- Size of remote file:
- 22 MB
- SHA256:
- f4ffb66611d6078dc2b0636f4ebe7a440432367bf35a5373950bbf2428c9a3ad
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