Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use Tensorride/Classifier_30k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tensorride/Classifier_30k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tensorride/Classifier_30k")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tensorride/Classifier_30k") model = AutoModelForSequenceClassification.from_pretrained("Tensorride/Classifier_30k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e2fc26d28751075d0b97f1aef7e13a48f044e0ccc1d3f8856c958f926464463
- Size of remote file:
- 1.74 GB
- SHA256:
- 2349dd499f02e7b112ec09a25779855b2ef9285138aed83d1fbc3e433d55ef88
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