Instructions to use JeremyNJ/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremyNJ/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremyNJ/test-trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremyNJ/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("JeremyNJ/test-trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from JeremyNJ/test-trainer: direct link, hf CLI and curl.
- Browser
- Download file 4.28 kB
-
https://huggingface.co/JeremyNJ/test-trainer/resolve/main/training_args.bin
- Command line
-
hf download hf://JeremyNJ/test-trainer/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/JeremyNJ/test-trainer/resolve/main/training_args.bin
4.28 kB
- Xet hash:
- 92fdc2b9f4babeb4f037ab9fdc622f9407369d68925c3af3d489a7c90c41876c
- Size of remote file:
- 4.28 kB
- SHA256:
- 8e4c2d8e6160a85479cb51e73fb5b10344e97fc716d78593fb118ef2c94217b2
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