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", device_map="auto")# 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
- Xet hash:
- 94dbd75a3e19ad6089c203a7dbe32fd338803ac15bdf7beada1ac3a723071ed9
- Size of remote file:
- 433 MB
- SHA256:
- 2e20fe197566dd74535b99664646f0e3942e262d0baceffd5bed5f2f09925919
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