Instructions to use MoritzLaurer/policy-distilbert-7d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoritzLaurer/policy-distilbert-7d with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MoritzLaurer/policy-distilbert-7d")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MoritzLaurer/policy-distilbert-7d") model = AutoModelForSequenceClassification.from_pretrained("MoritzLaurer/policy-distilbert-7d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0d4176407944b3b413a580032d77937cbcf34f2a216715941e325d68f877602
- Size of remote file:
- 268 MB
- SHA256:
- cd32dc60bbb4fbe37875748795abb074eb007a046050e903dce7803a2f10eff5
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