Instructions to use aomar85/fold_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aomar85/fold_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aomar85/fold_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aomar85/fold_1") model = AutoModelForSequenceClassification.from_pretrained("aomar85/fold_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aomar85/fold_1: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/aomar85/fold_1/resolve/main/training_args.bin
- Command line
-
hf download hf://aomar85/fold_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aomar85/fold_1/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 799753d780e570b498fb06819b5f5233ab6ee8290d8e633d99b1d2171fd744c1
- Size of remote file:
- 5.78 kB
- SHA256:
- a3d39ba0eb891b6dfff61d4291eaa946a86e2e924c387e4e92b6f90609109b3a
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