Instructions to use bqr5tf/ADRv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bqr5tf/ADRv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bqr5tf/ADRv3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bqr5tf/ADRv3") model = AutoModelForSequenceClassification.from_pretrained("bqr5tf/ADRv3") - 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 sha256:0c24db81e21206e391a5d6d1cf8fefcf7d0c8e63c421a6b32a27146b3d403c5a
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size 1624911240
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