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
redmoon-gibberishdetective / runs /Mar25_05-05-14_bc0f21d7af29 /events.out.tfevents.1742879321.bc0f21d7af29.739.1
- Xet hash:
- 3463934473315a4024f13d9bf15f3d45fa55bee1e339c5c2932f0bd32f8225ab
- Size of remote file:
- 6.51 kB
- SHA256:
- 5a1ab8680255ad428089ee5af329a0d42782b1fc80e916fbf97dc1eb9a8b0047
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.