Instructions to use blind-assist/internvl3-2b-walk-lora-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use blind-assist/internvl3-2b-walk-lora-v1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("OpenGVLab/InternVL3-2B") model = PeftModel.from_pretrained(base_model, "blind-assist/internvl3-2b-walk-lora-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dabb4110943c59d232d03402dd60c79bd44bb11b1c8f97da92e209523e531857
- Size of remote file:
- 295 MB
- SHA256:
- 9a884f9b7f1ade0bd37c7b499332568aa0d706aef17b0c8955e65335475d3bb7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.