Instructions to use davidna22/text-failed-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidna22/text-failed-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davidna22/text-failed-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davidna22/text-failed-classifier") model = AutoModelForSequenceClassification.from_pretrained("davidna22/text-failed-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05cd4bf2e410e3d9d0ca32a2bef1e614ece0b40b594e6f61a1e474440a462069
- Size of remote file:
- 499 MB
- SHA256:
- 5cafa7cb036e2062fd00d3a783c5f8d9f44c1cc20ec8308a76ea1f0a4e0c455b
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