Instructions to use SimpleJev/JevAny-Robotics-4B-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SimpleJev/JevAny-Robotics-4B-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Qwen/Qwen3.5-4B") model = PeftModel.from_pretrained(base_model, "SimpleJev/JevAny-Robotics-4B-LoRA") - Notebooks
- Google Colab
- Kaggle
Download head.pt from SimpleJev/JevAny-Robotics-4B-LoRA: direct link, hf CLI and curl.
- Browser
- Download file 5.51 MB
-
https://huggingface.co/SimpleJev/JevAny-Robotics-4B-LoRA/resolve/main/head.pt
- Command line
-
hf download hf://SimpleJev/JevAny-Robotics-4B-LoRA/head.pt
-
curl -L -o head.pt https://huggingface.co/SimpleJev/JevAny-Robotics-4B-LoRA/resolve/main/head.pt
5.51 MB
- Xet hash:
- 299c6a0fafad57308c3bcc0cf2e5478f288c66f0d981f4df21db438b42a379a6
- Size of remote file:
- 5.51 MB
- SHA256:
- c9452ec9bd01bbb2a88e8dab13451fb41d5254d36a45ecf164eac64da074f7be
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.