Instructions to use jkefeli/CancerStage_Classifier_T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jkefeli/CancerStage_Classifier_T with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jkefeli/CancerStage_Classifier_T")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jkefeli/CancerStage_Classifier_T") model = AutoModelForSequenceClassification.from_pretrained("jkefeli/CancerStage_Classifier_T", device_map="auto") - 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 sha256:3a1f9112cf3cf1c3dbf432e8847758f89f6afc6d23844de3eecb67b615473be7
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size 512306480
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