Instructions to use rollerhafeezh/fire-silvanus-quantization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rollerhafeezh/fire-silvanus-quantization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rollerhafeezh/fire-silvanus-quantization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rollerhafeezh/fire-silvanus-quantization") model = AutoModelForSequenceClassification.from_pretrained("rollerhafeezh/fire-silvanus-quantization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91cd64d614bbbd2fe25c0bf3e7dcd73a2f4d63fb8b6c622f5413efe414c98c75
- Size of remote file:
- 279 MB
- SHA256:
- db73b584417223b8ef9dad23bdc1b3eed447845b342fae493cabf7f4ab9fb852
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