Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
deberta-v3
subjectivity-detection
multilingual
sentiment-analysis
Instructions to use AIWizards/mdeberta-v3-base-subjectivity-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIWizards/mdeberta-v3-base-subjectivity-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AIWizards/mdeberta-v3-base-subjectivity-multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AIWizards/mdeberta-v3-base-subjectivity-multilingual") model = AutoModelForSequenceClassification.from_pretrained("AIWizards/mdeberta-v3-base-subjectivity-multilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35db3dcf6c1504b0f973635fd2a4715c10f74a73a735e37f5e56c898695bbfb3
- Size of remote file:
- 5.37 kB
- SHA256:
- 1aa1e0724b5e37efca848fed302a0a44288fd63c48cb457dcafc76b227a8bc46
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