Instructions to use raghavdw/cci-capstone-asapp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raghavdw/cci-capstone-asapp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="raghavdw/cci-capstone-asapp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("raghavdw/cci-capstone-asapp") model = AutoModelForSequenceClassification.from_pretrained("raghavdw/cci-capstone-asapp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e0c125efda3f82568c8a7fab71e81bc5b3177508c938fbd6851a12fa1770cdc
- Size of remote file:
- 5.3 kB
- SHA256:
- 91fcaabf344f40b0aa177724830cad507a49881d1fffcdbc010c4f7524cdfbbf
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