Instructions to use blepine/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blepine/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="blepine/test-trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("blepine/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("blepine/test-trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31bef101fe0e794e7fa3b7c0018f2c9b40394e1c1d2fa48daa54775421844778
- Size of remote file:
- 438 MB
- SHA256:
- 9d6909fd97c6f65f88c994fe6cd5eb57f704ae61b8a806efb16f3f8a51d3607b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.