Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use LibrAI/distilbert-action-ro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LibrAI/distilbert-action-ro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LibrAI/distilbert-action-ro")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LibrAI/distilbert-action-ro") model = AutoModelForSequenceClassification.from_pretrained("LibrAI/distilbert-action-ro") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d94d9375f6f1f14714065d7ad6468b3a5ee3c2d50194e5a168f14dd31c9dc47a
- Size of remote file:
- 3.96 kB
- SHA256:
- b1c4951f69a51388d4ed6742a3c9a4190df3f5d18dcd15f865466ae6dae6a9d6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.