Instructions to use ninja/final_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ninja/final_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ninja/final_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ninja/final_model") model = AutoModelForSequenceClassification.from_pretrained("ninja/final_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63f3a2efca11afe46cfb119596229e97b60856930597869206618988e29b4764
- Size of remote file:
- 435 MB
- SHA256:
- b73d1ffcc45c7b8b930568db2a5d14209cfd4af420fc05d2c1aa4dbf505d06e6
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