Instructions to use jg-glob/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jg-glob/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jg-glob/test-trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jg-glob/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("jg-glob/test-trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45b05cffd03eda52755a2f241155a0db11df4e781bc4aa1fdcd3c49e79416813
- Size of remote file:
- 5.11 kB
- SHA256:
- 11016f98727560a9ff6540eb033a824b0028884c36219a82d00221fe988d2cab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.