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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TrustSafeAI/RADAR-Vicuna-7B") model = AutoModelForSequenceClassification.from_pretrained("TrustSafeAI/RADAR-Vicuna-7B", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from TrustSafeAI/RADAR-Vicuna-7B: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
-
https://huggingface.co/TrustSafeAI/RADAR-Vicuna-7B/resolve/main/tokenizer.json
- Command line
-
hf download hf://TrustSafeAI/RADAR-Vicuna-7B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/TrustSafeAI/RADAR-Vicuna-7B/resolve/main/tokenizer.json
1.36 MB
File too large to display, you can check the raw version instead.