Instructions to use tkuye/tiny-jdc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tkuye/tiny-jdc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tkuye/tiny-jdc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tkuye/tiny-jdc") model = AutoModelForSequenceClassification.from_pretrained("tkuye/tiny-jdc") - 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 sha256:6d1b6417e01f89cf9b6ab60eb840d475f73aad6cc2e3b826d7200cc258e429fa
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size 360668
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