Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use shayonhuggingface/videberta-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shayonhuggingface/videberta-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shayonhuggingface/videberta-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shayonhuggingface/videberta-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("shayonhuggingface/videberta-sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d368dc8cfd1d9034203c16a697fee7333f419033f6c319fd9f34f62f9ddf6a7
- Size of remote file:
- 283 MB
- SHA256:
- 8e077887932329a3d0ff152d7dba08540f29944331ccdc4f7689df0637252568
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