Instructions to use gechim/cls-metadaweb-dataGemini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gechim/cls-metadaweb-dataGemini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gechim/cls-metadaweb-dataGemini")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gechim/cls-metadaweb-dataGemini") model = AutoModelForSequenceClassification.from_pretrained("gechim/cls-metadaweb-dataGemini") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 18ac18e7f9252fdef74b558906ef258dc689719fafdd26158c8d4a900c09b8c6
- Size of remote file:
- 5.05 kB
- SHA256:
- 4821f1e6213b7332ff49f9b725f6337e9cd053f0afcc2e46698b11c68153afe6
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