Instructions to use Rifky/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rifky/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rifky/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Rifky/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("Rifky/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4b9dc969b9fb33c01e696da2f4819b6c4f936ca690b4cfe7d3232fec4247d3e
- Size of remote file:
- 4.09 kB
- SHA256:
- f5491189832f585cf2d99b4fae594e754df81525f1e06854b88541f1d36578fc
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