Instructions to use Devishetty100/redmoon-gibberishdetective with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devishetty100/redmoon-gibberishdetective with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Devishetty100/redmoon-gibberishdetective")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Devishetty100/redmoon-gibberishdetective") model = AutoModelForSequenceClassification.from_pretrained("Devishetty100/redmoon-gibberishdetective") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be5fcb5b144a460268d79f471cfb104a648fd4775bc1ecdc8e7f494414ef8897
- Size of remote file:
- 268 MB
- SHA256:
- e4ffab9e6fbb8286b9ad35ace56aa0830b40bd802e1877a45b63acf1c9bf11b0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.