Instructions to use VaAishvarR/ADRv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VaAishvarR/ADRv1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VaAishvarR/ADRv1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VaAishvarR/ADRv1") model = AutoModelForSequenceClassification.from_pretrained("VaAishvarR/ADRv1") - 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 sha256:01231a3120941413a03881b223058f66e9a2ec5f8b061e91a79a51eb383d88d1
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size 433274952
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