Instructions to use KobanBanan/out with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KobanBanan/out with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KobanBanan/out")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KobanBanan/out") model = AutoModelForSequenceClassification.from_pretrained("KobanBanan/out", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98c380284a034cba2e1c85089e6421d1bb9400badc1eb134c4cc5f984a5adf19
- Size of remote file:
- 3.96 kB
- SHA256:
- 3ebc850de334c53998f7aaada671a9e089214d7fca6f68a0fa3e9a80ae3fa0ce
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