Instructions to use prane-eth/Large-Supervisor-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prane-eth/Large-Supervisor-Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prane-eth/Large-Supervisor-Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prane-eth/Large-Supervisor-Model") model = AutoModelForSequenceClassification.from_pretrained("prane-eth/Large-Supervisor-Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13660949184e065f65400263433ff51fab526214cd5f61386d533f9554b991e6
- Size of remote file:
- 268 MB
- SHA256:
- 868002c7ed54c744be07e0cfc52d782f13c4148935212ab9fc0cd364a6504d90
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