Instructions to use nruigrok/verbindend with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nruigrok/verbindend with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nruigrok/verbindend")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nruigrok/verbindend") model = AutoModelForSequenceClassification.from_pretrained("nruigrok/verbindend", device_map="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 sha256:1d199ef4dfac6df0e3709b3e0ece2e9410fdb3be1df4a7733c7da3f410da97bc
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size 436583504
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