Instructions to use GD/cq-bert-model-repo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GD/cq-bert-model-repo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GD/cq-bert-model-repo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GD/cq-bert-model-repo") model = AutoModelForSequenceClassification.from_pretrained("GD/cq-bert-model-repo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 729411ba1418fa3bbb279dc8c3ce34b6b28fd23ff5f8d99d3e7b6a6f2452e92a
- Size of remote file:
- 1.64 kB
- SHA256:
- 46104c1ab0ae348ceae93b57ad5b5782e104bb6ab59370beb6de0ebd254c3a4d
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