Instructions to use SushantGautam/LogClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SushantGautam/LogClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SushantGautam/LogClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SushantGautam/LogClassification") model = AutoModelForSequenceClassification.from_pretrained("SushantGautam/LogClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a5be54612cfecd2bc120f6aaf865c453274f00959234bdfbd5665c6bb103196
- Size of remote file:
- 17.1 MB
- SHA256:
- 1d58a68c276b56fcc48c165c63f70e5e4d452b4182032a5f7a2d018f4aa1a889
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.