Instructions to use Ashed00/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ashed00/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ashed00/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ashed00/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("Ashed00/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 100805f0c4cefe9b89327977fb1e4ebc7a2b7145ab3512b8afd360e8b2d6afb1
- Size of remote file:
- 5.11 kB
- SHA256:
- 8efbfa26017f672231817a40a28611d1aea80e9eedf17b942c047faf72d72fc2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.