Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use DanielViniciusAlves/outputs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DanielViniciusAlves/outputs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DanielViniciusAlves/outputs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DanielViniciusAlves/outputs") model = AutoModelForSequenceClassification.from_pretrained("DanielViniciusAlves/outputs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56dafb31cf428c52bf5c78c0e9acfe7b48e74c6850807e8606b74ed0b71a1f12
- Size of remote file:
- 3.25 kB
- SHA256:
- 1e5b93efd6a046a872e6d0e25dade4ffe6ac614f26b56394c7ff28c0ab179050
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