Image-Text-to-Text
PEFT
Safetensors
English
lora
vise
self-evolving
multimodal
vision-language
lmm
visual-grounding
image-captioning
qwen3-vl
unsupervised
conversational
Instructions to use shravvvv/VISE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shravvvv/VISE with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-VL-2B-Instruct") model = PeftModel.from_pretrained(base_model, "shravvvv/VISE") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 693ec4b3922b0bd306bf7b4989e115ffbfeb7b0c08b31bc6d956818c6bb07f61
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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