Instructions to use ElMad/trusting-cod-535 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElMad/trusting-cod-535 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ElMad/trusting-cod-535")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ElMad/trusting-cod-535") model = AutoModelForSequenceClassification.from_pretrained("ElMad/trusting-cod-535", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ElMad/trusting-cod-535: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/ElMad/trusting-cod-535/resolve/main/training_args.bin
- Command line
-
hf download hf://ElMad/trusting-cod-535/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ElMad/trusting-cod-535/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- f52e76abc3825077ab30466e69262e2d8f2ee09317e1237271f6e2d93195466e
- Size of remote file:
- 5.5 kB
- SHA256:
- 5a6a34534b654750adcdd32297cf21c9e0e653ee119ac241268f50ad812105b7
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