Instructions to use overfly83/test-classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use overfly83/test-classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="overfly83/test-classification-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("overfly83/test-classification-model") model = AutoModelForSequenceClassification.from_pretrained("overfly83/test-classification-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fcd7693234028899a677e0bc3706501753ad566c3e67e8b1f9b2560160293e2
- Size of remote file:
- 3.58 kB
- SHA256:
- df0550a50042593e7274af0c0ad4dbe690d0d407a5f2fd3051e02e47bed1a8a3
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