Instructions to use roadrage10/RADAR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roadrage10/RADAR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="roadrage10/RADAR", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("roadrage10/RADAR", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from roadrage10/RADAR: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/roadrage10/RADAR/resolve/main/tokenizer.json
- Command line
-
hf download hf://roadrage10/RADAR/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/roadrage10/RADAR/resolve/main/tokenizer.json
3.58 MB
File too large to display, you can check the raw version instead.