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:
- 573fa4c6994a5d1f797995d5d77a00c9e2475b5a7160637917ea90c4bc1f94b5
- Size of remote file:
- 4.93 GB
- SHA256:
- 123a29674ef0596e4596435ed81339ececd106673219076b7c83994a70c47c03
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