Instructions to use cruiser/distilbert_final_config_dropout with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cruiser/distilbert_final_config_dropout with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cruiser/distilbert_final_config_dropout")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cruiser/distilbert_final_config_dropout") model = AutoModelForSequenceClassification.from_pretrained("cruiser/distilbert_final_config_dropout", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5127b180a7f7b096387d6c88382a85bdd09c68725d56328c5ba57aa7dcc90ca9
- Size of remote file:
- 3.64 kB
- SHA256:
- eb6f93d1aa0603bc278729817f19c12ec0e0cb34b31836f19452b1b45df12e00
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