Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use wnic00/distilbert-p1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wnic00/distilbert-p1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wnic00/distilbert-p1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wnic00/distilbert-p1") model = AutoModelForSequenceClassification.from_pretrained("wnic00/distilbert-p1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06d338d6af76a95c3fd9d976d1f7a0b1046fba80245e7902850d0f0e09579798
- Size of remote file:
- 3.96 kB
- SHA256:
- a962f8acbf9b3dc98a21d6525a1567504fb589f10534966102e3d5f7780a4e3b
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