Image-Text-to-Text
PEFT
Safetensors
English
vision-language
blockchain-security
attack-detection
lora
agentic-economy
dogon
rocm
amd
conversational
Instructions to use Ibonon/imina_na_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ibonon/imina_na_lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-VL-2B-Instruct") model = PeftModel.from_pretrained(base_model, "Ibonon/imina_na_lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 940c809978ca589e4c2f81c5579fef3317f47808d4b3e5ec20cb073b7c1bae40
- Size of remote file:
- 35 MB
- SHA256:
- dd4026d76297c2810575ea0ffbe57a4b1b06507289503275d2adfc9b5073f65b
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