Instructions to use prakod/Llama-3.2-3B-cline-osn-roman with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prakod/Llama-3.2-3B-cline-osn-roman with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prakod/Llama-3.2-3B-cline-osn-roman")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prakod/Llama-3.2-3B-cline-osn-roman") model = AutoModelForSequenceClassification.from_pretrained("prakod/Llama-3.2-3B-cline-osn-roman") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a744b2108390faef45656bdbd57ba8a118f3a51752f060932511fbbe685a91bc
- Size of remote file:
- 2.92 GB
- SHA256:
- 786ee2cbafb19cb6a50d57746acb9a141a6c49967bb5f63cbad60f12cfb258d1
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