Instructions to use toure5013/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toure5013/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="toure5013/test-trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("toure5013/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("toure5013/test-trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 500034618ec10be065f54c4193621ef212aa538317ccb7915d5a43a7dbaca8e4
- Size of remote file:
- 5.71 kB
- SHA256:
- b40ebdadea83241fb9bd7f74ac242ba308aad71960b6ad81389b780efd0be049
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.