Instructions to use keonju/classificationmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keonju/classificationmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keonju/classificationmodel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("keonju/classificationmodel") model = AutoModelForSequenceClassification.from_pretrained("keonju/classificationmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2dced4d5dd100a0c874b8ee92b2f8e20bd6bcabeb7874124f4642b23a374f12
- Size of remote file:
- 498 MB
- SHA256:
- 9fb970746efaad9b4a0ef82e12ac42fdaa804552221522951dff88beac90b9a6
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