Text Classification
Transformers
Safetensors
deberta-v2
formal or informal classification
sentiment-analysis
text-embeddings-inference
Instructions to use LenDigLearn/formality-classifier-mdeberta-v3-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LenDigLearn/formality-classifier-mdeberta-v3-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LenDigLearn/formality-classifier-mdeberta-v3-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LenDigLearn/formality-classifier-mdeberta-v3-base") model = AutoModelForSequenceClassification.from_pretrained("LenDigLearn/formality-classifier-mdeberta-v3-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download confusion_matrix.svg from LenDigLearn/formality-classifier-mdeberta-v3-base: direct link, hf CLI and curl.
- Browser
- Download file 30.2 kB
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https://huggingface.co/LenDigLearn/formality-classifier-mdeberta-v3-base/resolve/main/confusion_matrix.svg
- Command line
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hf download hf://LenDigLearn/formality-classifier-mdeberta-v3-base/confusion_matrix.svg
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curl -L -o confusion_matrix.svg https://huggingface.co/LenDigLearn/formality-classifier-mdeberta-v3-base/resolve/main/confusion_matrix.svg
30.2 kB