Instructions to use P829692/thesis-model-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use P829692/thesis-model-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="P829692/thesis-model-1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("P829692/thesis-model-1") model = AutoModelForTokenClassification.from_pretrained("P829692/thesis-model-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f16973f4d65ff139d0d6be5862138df9803e351f009033fa5f3154841395de27
- Size of remote file:
- 436 MB
- SHA256:
- f2c8811cdddcb14db7f3a8637a9635921070d889064250b53b4ecde696a1564a
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