Instructions to use rollerhafeezh/language-silvanus-quantization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rollerhafeezh/language-silvanus-quantization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rollerhafeezh/language-silvanus-quantization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rollerhafeezh/language-silvanus-quantization") model = AutoModelForSequenceClassification.from_pretrained("rollerhafeezh/language-silvanus-quantization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ae419a5b5495ea3f1d75d9aa47e04bfa4901885c24981b359296b59dbcce5be
- Size of remote file:
- 279 MB
- SHA256:
- 120c16e1665ffc928a657615ee0f759f7ddd4c316881766e8de13cfb051edfbe
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