Instructions to use research-dump/distilbert_base_cased_temp_classifier_bootstrapped with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/distilbert_base_cased_temp_classifier_bootstrapped with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/distilbert_base_cased_temp_classifier_bootstrapped")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/distilbert_base_cased_temp_classifier_bootstrapped") model = AutoModelForSequenceClassification.from_pretrained("research-dump/distilbert_base_cased_temp_classifier_bootstrapped") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3304bafa5b9de96c91455fa94e8c29e299dbbfdce62d74478ede690466ccf148
- Size of remote file:
- 263 MB
- SHA256:
- e23ee86ea16033b8aeda03a982f8b25a3a133b8d8cab1b3f1c39d2a9099958cd
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