Image-Text-to-Text
PEFT
Safetensors
graph-learning
multimodal-graphs
vision-language-model
qwen-vl
lora
node-classification
link-prediction
Instructions to use oofwite/OMG-VLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use oofwite/OMG-VLM with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-VL-Chat") model = PeftModel.from_pretrained(base_model, "oofwite/OMG-VLM") - Notebooks
- Google Colab
- Kaggle
Download textual_aggregation.pth from oofwite/OMG-VLM: direct link, hf CLI and curl.
- Browser
- Download file 3.56 GB
-
https://huggingface.co/oofwite/OMG-VLM/resolve/main/textual_aggregation.pth
- Command line
-
hf download hf://oofwite/OMG-VLM/textual_aggregation.pth
-
curl -L -o textual_aggregation.pth https://huggingface.co/oofwite/OMG-VLM/resolve/main/textual_aggregation.pth
3.56 GB
- Xet hash:
- da40aadc4fad78aa5017b88c81d4e1f7b683fb42bcd28568e45a439fb7556955
- Size of remote file:
- 3.56 GB
- SHA256:
- 3f4b25c4395316a24a3f0c1cbb28157204703e3cb3a146c74c7c318c82542859
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