Instructions to use begnini/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use begnini/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="begnini/test_trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("begnini/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("begnini/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from begnini/test_trainer: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/begnini/test_trainer/resolve/main/training_args.bin
- Command line
-
hf download hf://begnini/test_trainer/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/begnini/test_trainer/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 9521f5acf16a5a035a5686533fc6aff7bbcc5fcefb98f5e6b5747e4e2b3bb152
- Size of remote file:
- 4.54 kB
- SHA256:
- d4be2e345b5e1ce2b6dcd3fcdd88565f35f0c07f986815f2f32e3e951aa368af
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