Instructions to use ronaldahmed/ccl_win-plos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ronaldahmed/ccl_win-plos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ronaldahmed/ccl_win-plos")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ronaldahmed/ccl_win-plos") model = AutoModelForSequenceClassification.from_pretrained("ronaldahmed/ccl_win-plos") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 528fecbfeed9b5fd8eb11c19be9051b021b28bfebeb705c408fa5228dc8c066b
- Size of remote file:
- 1.42 GB
- SHA256:
- 5a1115915608f02c93e012ec5746c65be06c2b6d8ee5f88d3dba5ffb1c8fa203
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