Instructions to use lsb/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lsb/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lsb/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lsb/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("lsb/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 793681d13203ea17a04276e4fbc0e5e92b14013c19f8b9af7d234d31f6481cd7
- Size of remote file:
- 4.92 kB
- SHA256:
- 8b5d5bb6821e2bde5903533a318f7104e53ed84888aafbc7084c08050c28f81f
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