Instructions to use LexFerrinson/FirulaiModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LexFerrinson/FirulaiModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="LexFerrinson/FirulaiModel")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("LexFerrinson/FirulaiModel") model = AutoModelForTokenClassification.from_pretrained("LexFerrinson/FirulaiModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14d4c4ad01bf9eff95a8d15b3444ca9102f65f91645c1e215067547cf17f973d
- Size of remote file:
- 266 MB
- SHA256:
- da2abbb86c7e87b3faf357c51446bf883932a8f39f92446f12440d3a3803a1e2
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