Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use abandekar-dev/distilbert-onet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abandekar-dev/distilbert-onet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abandekar-dev/distilbert-onet")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abandekar-dev/distilbert-onet") model = AutoModelForSequenceClassification.from_pretrained("abandekar-dev/distilbert-onet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e2b38ba9740df7921e9bbba5981efff2d23f78d56f90c150741ead6078ff004
- Size of remote file:
- 5.2 kB
- SHA256:
- 8c9d7e309f9ac992b564bd7115868cb6cbb8d4a8b55ed9f150b7df03502c9e20
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