Instructions to use pbeyens/RandomCropped-repo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pbeyens/RandomCropped-repo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pbeyens/RandomCropped-repo")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pbeyens/RandomCropped-repo") model = AutoModelForTokenClassification.from_pretrained("pbeyens/RandomCropped-repo") - 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:b5ff95ff3c325b6789a5e8b457f85c75679bb761f124987254522001e53d4c86
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size 520793292
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