Instructions to use ElMad/fun-wolf-403 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElMad/fun-wolf-403 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ElMad/fun-wolf-403")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ElMad/fun-wolf-403") model = AutoModelForSequenceClassification.from_pretrained("ElMad/fun-wolf-403", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ElMad/fun-wolf-403: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/ElMad/fun-wolf-403/resolve/main/training_args.bin
- Command line
-
hf download hf://ElMad/fun-wolf-403/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ElMad/fun-wolf-403/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- c7d1cbcd003135e8672368e9d48ea30ef86f87162984f0d6d08c0add374d7d6f
- Size of remote file:
- 5.37 kB
- SHA256:
- 5ed648312f35d39322e82bf6799834ab8f898444bd5e4fd9ea49513636ed509a
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