Instructions to use rpii2023/finale with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rpii2023/finale with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rpii2023/finale")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("rpii2023/finale") model = AutoModelForTokenClassification.from_pretrained("rpii2023/finale") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5b61eaca425c9c25b4d534ae5ac4e70cc004f7fcd8c0cee66409090e3c8b489e
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size 1428607236
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