Instructions to use rollerhafeezh/ner-silvanus-quantization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rollerhafeezh/ner-silvanus-quantization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rollerhafeezh/ner-silvanus-quantization")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rollerhafeezh/ner-silvanus-quantization") model = AutoModelForTokenClassification.from_pretrained("rollerhafeezh/ner-silvanus-quantization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a484d5f0048c3d32308e87c55a875fd8f2049263913d48b9268d49c1e5e23e0b
- Size of remote file:
- 279 MB
- SHA256:
- d8efea957fa6e0d4fd103e217493fd0b840158638bd855ebe52668ee389f2e4b
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