Instructions to use adriansanz/test3_balancedsmall with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adriansanz/test3_balancedsmall with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adriansanz/test3_balancedsmall")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adriansanz/test3_balancedsmall") model = AutoModelForSequenceClassification.from_pretrained("adriansanz/test3_balancedsmall", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from adriansanz/test3_balancedsmall: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/adriansanz/test3_balancedsmall/resolve/main/training_args.bin
- Command line
-
hf download hf://adriansanz/test3_balancedsmall/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/adriansanz/test3_balancedsmall/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 81d1a22e08c0160e9ccb796be250ec14c352fe78a4278adf56bce65e45c93420
- Size of remote file:
- 4.92 kB
- SHA256:
- ece5664ef1583e50d6725134fa35534b32d881dbaa402f0e16d2c86df8140032
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