Instructions to use APudding/bigcode-starcoderbase-1b-finetuned-defect-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use APudding/bigcode-starcoderbase-1b-finetuned-defect-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="APudding/bigcode-starcoderbase-1b-finetuned-defect-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("APudding/bigcode-starcoderbase-1b-finetuned-defect-detection") model = AutoModelForSequenceClassification.from_pretrained("APudding/bigcode-starcoderbase-1b-finetuned-defect-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34530ab3a84db2844326e0eda3199736d62ef085cbd7590b9c38faa98a30a690
- Size of remote file:
- 4.55 GB
- SHA256:
- 57cfd0c1e5369cbe168d7d6d1a0fc81a7a9588feb1474d9895ff94bcbf638e17
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