Instructions to use Ridhwan/locum_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ridhwan/locum_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ridhwan/locum_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ridhwan/locum_classification") model = AutoModelForSequenceClassification.from_pretrained("Ridhwan/locum_classification") - 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:b4aeb096d5ded2cf84080ea4d3899c51baedf57f622710d73aa79d10f6186d59
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size 267841796
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