Image-Text-to-Text
PEFT
Safetensors
lora
multimodal
vision-language
uav
aerial
visual-question-answering
multi-agent-perception
conversational
Instructions to use EasonFan/aircop-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use EasonFan/aircop-7b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/hpc2hdd/home/yfan546/data/hf_cache/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/cc594898137f460bfe9f0759e9844b3ce807cfb5") model = PeftModel.from_pretrained(base_model, "EasonFan/aircop-7b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bd2f092eeec244c0448f13e31edd4b25e625568713e4155993a3dea90c7437a
- Size of remote file:
- 11.4 MB
- SHA256:
- 9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
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