Instructions to use wu981526092/Sentence-Level-Stereotype-Detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wu981526092/Sentence-Level-Stereotype-Detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wu981526092/Sentence-Level-Stereotype-Detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wu981526092/Sentence-Level-Stereotype-Detector") model = AutoModelForSequenceClassification.from_pretrained("wu981526092/Sentence-Level-Stereotype-Detector", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44954b2ad641a7913f2e713432f239b9435e8077c4644e3baebb53ff97f8fdf2
- Size of remote file:
- 627 Bytes
- SHA256:
- cf7f11b4a721200e4855c318b8001b95008046cba699011100f3bf012c01c546
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.