Instructions to use trevrock/ADRv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trevrock/ADRv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="trevrock/ADRv2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("trevrock/ADRv2") model = AutoModelForSequenceClassification.from_pretrained("trevrock/ADRv2") - 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 sha256:0b8a8fd3c1f7b405cc58132e451846f9394ee9a9cedabade55eb380e9f53075d
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size 556803760
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