Instructions to use ljh1/hello-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ljh1/hello-custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ljh1/hello-custom")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ljh1/hello-custom") model = AutoModelForSequenceClassification.from_pretrained("ljh1/hello-custom") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80e87e908d165644f56d0cf8e0a9b91f73e50483f277b45ec9abfd4fca63b1f1
- Size of remote file:
- 268 MB
- SHA256:
- 5aa7398d830fcc94f95af88d7cc3013813668cfc58a07d75a8116cfd8af75c4d
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