Instructions to use parkth/ai.keepit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use parkth/ai.keepit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="parkth/ai.keepit")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("parkth/ai.keepit") model = AutoModelForSequenceClassification.from_pretrained("parkth/ai.keepit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 999394a31c452919d3baac99a0c072e0c30e72c6744d24843dd1e9bbc3b04a07
- Size of remote file:
- 436 MB
- SHA256:
- a828d3e80ab6f59d629270ea98c12509e738ec29bbb83e907ba2162622db111b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.