Instructions to use VinsmokeMir/SC_OurModel_E10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VinsmokeMir/SC_OurModel_E10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VinsmokeMir/SC_OurModel_E10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VinsmokeMir/SC_OurModel_E10") model = AutoModelForSequenceClassification.from_pretrained("VinsmokeMir/SC_OurModel_E10") - 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 sha256:92064006ecff60ed9f9c73050276759b894ae21e662e461309d557fd3fceb0ad
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size 83258212
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