Instructions to use RafatK/Cascade-Gemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RafatK/Cascade-Gemma with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-3-4b-it") model = PeftModel.from_pretrained(base_model, "RafatK/Cascade-Gemma") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from RafatK/Cascade-Gemma: direct link, hf CLI and curl.
- Browser
- Download file 70 Bytes
-
https://huggingface.co/RafatK/Cascade-Gemma/resolve/main/processor_config.json
- Command line
-
hf download hf://RafatK/Cascade-Gemma/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/RafatK/Cascade-Gemma/resolve/main/processor_config.json
70 Bytes
| { | |
| "image_seq_length": 256, | |
| "processor_class": "Gemma3Processor" | |
| } | |