Instructions to use jnwnlee/distbert_cpcd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jnwnlee/distbert_cpcd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jnwnlee/distbert_cpcd")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jnwnlee/distbert_cpcd") model = AutoModelForSequenceClassification.from_pretrained("jnwnlee/distbert_cpcd") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a7a6dff427a0ddc6eecd8481f0c4389e9a8d8c0df6019ffa3e65488c7a7c53d
- Size of remote file:
- 268 MB
- SHA256:
- 8d1518358954b6883de9d7125a61abab5e6d65d625927c05c3522d5d3a0005d1
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