Instructions to use timonziegenbein/appropriateness-classifier-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use timonziegenbein/appropriateness-classifier-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="timonziegenbein/appropriateness-classifier-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("timonziegenbein/appropriateness-classifier-binary") model = AutoModelForSequenceClassification.from_pretrained("timonziegenbein/appropriateness-classifier-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3a15cb5d40ce9534e35bcbfd042ab68fea3efed6a3823c8ccb9b9d396e9ea13
- Size of remote file:
- 3.48 GB
- SHA256:
- 25325f6ddb6ff56a0cbdbab4757cbd99070f039ee44fa6cbb436416825e15442
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