Instructions to use Davegd/distillbert_complaints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davegd/distillbert_complaints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Davegd/distillbert_complaints")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Davegd/distillbert_complaints") model = AutoModelForSequenceClassification.from_pretrained("Davegd/distillbert_complaints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b84add5a9069d49923c6f519951a975da799bb294b834afd1f162c649abba347
- Size of remote file:
- 268 MB
- SHA256:
- 67a7fbeb7f69f981dcea15a59d43b29da31353ba513001e6c29f5d81dd718f98
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