Instructions to use nrsmac/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nrsmac/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nrsmac/test_trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nrsmac/test_trainer") model = AutoModel.from_pretrained("nrsmac/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nrsmac/test_trainer: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/nrsmac/test_trainer/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://nrsmac/test_trainer@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nrsmac/test_trainer/resolve/refs%2Fpr%2F1/training_args.bin
3.39 kB
- Xet hash:
- cc7f18b65330a4ff24d054be9fb68cffd3e6e7cf9e6aa5b8160c37ac49ac0040
- Size of remote file:
- 3.39 kB
- SHA256:
- 8a3e6b2b251996c197a2fc341e7864b7871e08b8998c6e1fb2a73f445de44625
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