Instructions to use sabaridsnfuji/FloorPlanVisionAIAdaptor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sabaridsnfuji/FloorPlanVisionAIAdaptor with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3.2-11b-vision-instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "sabaridsnfuji/FloorPlanVisionAIAdaptor") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sabaridsnfuji/FloorPlanVisionAIAdaptor: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/sabaridsnfuji/FloorPlanVisionAIAdaptor/resolve/main/tokenizer.json
- Command line
-
hf download hf://sabaridsnfuji/FloorPlanVisionAIAdaptor/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/sabaridsnfuji/FloorPlanVisionAIAdaptor/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 6fa041e2fbc7a16e7643f3e3e5e98c5a5ef9dee2866cdb7a1a679ad9c059a731
- Size of remote file:
- 17.2 MB
- SHA256:
- abd08b46c9c01a903788030f36d9731aad064d0c420e66b88e3e143cda9e4e9a
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