Instructions to use radned/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radned/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="radned/test-trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("radned/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("radned/test-trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from radned/test-trainer: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/radned/test-trainer/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://radned/test-trainer@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/radned/test-trainer/resolve/refs%2Fpr%2F2/training_args.bin
3.58 kB
- Xet hash:
- 7dc539719dde794fbc44393ea1e29a9074e9679936e2be8f0ed6c86bda5d30b8
- Size of remote file:
- 3.58 kB
- SHA256:
- 0f1d87f07275bd8115373f6e9ec1a64a1c968a971bf826e9bd03d0df0d4bbee2
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