Instructions to use TomUdale/sec_example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomUdale/sec_example with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="TomUdale/sec_example")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("TomUdale/sec_example") model = AutoModelForTokenClassification.from_pretrained("TomUdale/sec_example") - 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 sha256:6bc95389a52e44706b54cbca932c0dbabe9fe37a75c56df33fda582e70661998
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size 265491548
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