Image-Text-to-Text
PEFT
Safetensors
English
qlora
lora
vision-language
bug-triage
severity-classification
qwen2.5-vl
conversational
Instructions to use tathadn/visiontriage-config-c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tathadn/visiontriage-config-c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct") model = PeftModel.from_pretrained(base_model, "tathadn/visiontriage-config-c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6edb3b03a870a0b42eaf797c4b81f2cfb0469f2631a7b2c7740241f4e6357ca
- Size of remote file:
- 11.4 MB
- SHA256:
- c47a17a5ec1c2cdadb68a727e1fa12b6ff89fd89a67b136eda88b4c91d267714
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.