Instructions to use sdinger/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sdinger/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sdinger/dummy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sdinger/dummy-model") model = AutoModelForSequenceClassification.from_pretrained("sdinger/dummy-model") - 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 sha256:6a5f63dd6862abc66a7a7c820149904f5d95aadf49b11f56a1b2b24cb3ae7421
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size 437958648
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