Instructions to use harsh13333/gemma-clip-vqa_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harsh13333/gemma-clip-vqa_v1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import GemmaCLIPVLM model = GemmaCLIPVLM.from_pretrained("harsh13333/gemma-clip-vqa_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from harsh13333/gemma-clip-vqa_v1: direct link, hf CLI and curl.
- Browser
- Download file 1.16 MB
-
https://huggingface.co/harsh13333/gemma-clip-vqa_v1/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://harsh13333/gemma-clip-vqa_v1/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/harsh13333/gemma-clip-vqa_v1/resolve/main/tokenizer_config.json
1.16 MB
File too large to display, you can check the raw version instead.