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:
- 558fd9e26600fd6d9a30d046ff33f644fa0561ccac90fa63745328926b463f00
- Size of remote file:
- 3.96 kB
- SHA256:
- 4e84fa58cd81b128f7ce51f1e1a6a0009d7c3df0ddbe387e3adabea673c1f051
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