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:
- be0e6a859ae00f55ac08806a17e584b645c1c1dfb1f15f1cea1ae6c2c85b2c1b
- Size of remote file:
- 541 MB
- SHA256:
- ba8a29c03ba79fc67c5abaacdc09ce6533f182eb57145d6a01ea382f13f9433c
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