Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use wnic00/distilbert-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wnic00/distilbert-new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wnic00/distilbert-new")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wnic00/distilbert-new") model = AutoModelForSequenceClassification.from_pretrained("wnic00/distilbert-new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a816bc1f561c4382ef3c387d20b65aea746518a83f6544334d69f50e4e7930d1
- Size of remote file:
- 541 MB
- SHA256:
- 5f77f359fd56096f89a54eebc609ee71b16f5902e40594ace400589027af6f0b
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