Instructions to use hf-tiny-model-private/tiny-random-NezhaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-NezhaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-NezhaForSequenceClassification")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-NezhaForSequenceClassification", dtype="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 sha256:7f6a31139654e8ff5da9afcaac53b621aad55871c81abb79e9bd2ba5db061ec1
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size 2918412
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