Text Classification
Transformers
Safetensors
English
deberta-v2
subjectivity-detection
news-articles
Eval Results (legacy)
Instructions to use AIWizards/mdeberta-v3-base-subjectivity-english with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIWizards/mdeberta-v3-base-subjectivity-english with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AIWizards/mdeberta-v3-base-subjectivity-english")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AIWizards/mdeberta-v3-base-subjectivity-english") model = AutoModelForSequenceClassification.from_pretrained("AIWizards/mdeberta-v3-base-subjectivity-english", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09e56881aec9b37d49db2831975e5b70895a86c0cc9904b427e3d631d5681267
- Size of remote file:
- 5.37 kB
- SHA256:
- 32147bfa33e8322e06816e4882830b007cf47014167cd6bcfb04502ef707f8c6
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