Instructions to use Adilmar/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adilmar/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Adilmar/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Adilmar/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("Adilmar/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96fbb4dd91714bd4904791385894b10105f309277ba3fd2654439e23ff9d855e
- Size of remote file:
- 433 MB
- SHA256:
- f949f2618f912476d82124da2ba7a715af143d847814b060ac253f11cdf01030
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