Instructions to use ishanmakkar/visual-grounding-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ishanmakkar/visual-grounding-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-VL-7B-Instruct") model = PeftModel.from_pretrained(base_model, "ishanmakkar/visual-grounding-adapter") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ishanmakkar/visual-grounding-adapter: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/ishanmakkar/visual-grounding-adapter/resolve/main/tokenizer.json
- Command line
-
hf download hf://ishanmakkar/visual-grounding-adapter/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ishanmakkar/visual-grounding-adapter/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 47f88c16dc1b279edef7550d17fa1089b88c3bec018ec466aced15a12a98259a
- Size of remote file:
- 11.4 MB
- SHA256:
- 88a3a6fcb80132f76da8aa40cdc3fccd7e5d8468ef15421f5b0c2715e85217d2
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