Instructions to use TrustSafeAI/RADAR-Vicuna-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TrustSafeAI/RADAR-Vicuna-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TrustSafeAI/RADAR-Vicuna-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TrustSafeAI/RADAR-Vicuna-7B") model = AutoModelForSequenceClassification.from_pretrained("TrustSafeAI/RADAR-Vicuna-7B") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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 sha256:51487c4ba6b304be517899add360bffdaadb4d2fabe53d1b762f77d75db962e2
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size 1421499616
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