Instructions to use xshubhamx/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xshubhamx/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xshubhamx/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xshubhamx/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("xshubhamx/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ba8d0aafa9a423d6ddda94b1794d07cfb7e5de10e29676e9af046fb3251f10c
- Size of remote file:
- 4.92 kB
- SHA256:
- d8dc61e39a96655f71ceb72ce09d1ef63dea43efacf66848ad588289147f3b3e
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