Instructions to use DevxAman/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DevxAman/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DevxAman/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DevxAman/results") model = AutoModelForSequenceClassification.from_pretrained("DevxAman/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97a7e35d26ce34ae21a92c294613517f812a348ac241b75baf0ceaf2eb0b07e0
- Size of remote file:
- 5.14 kB
- SHA256:
- c8c5877aab711f0f83e7d33bfe55b606930ffa3d05ee9e725cc7e43d5a6221a7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.