Instructions to use sanjaycode/demo_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanjaycode/demo_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sanjaycode/demo_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sanjaycode/demo_model") model = AutoModelForSequenceClassification.from_pretrained("sanjaycode/demo_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eae173a8da4b13c1538bf382771aed02f8d52a9a52b553586a9e4087fccf1993
- Size of remote file:
- 438 MB
- SHA256:
- aca00222014221093c7d34515b0b4bdbc6c0f257b11cd55258d2adbf45474386
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