Image-Text-to-Text
PEFT
Safetensors
laboratory
protocol-aligned-action-prediction
lora
qwen
long-horizon-planning
conversational
Instructions to use Stanford-CongLab/LabHorizon-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Stanford-CongLab/LabHorizon-Model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.6-35B-A3B") model = PeftModel.from_pretrained(base_model, "Stanford-CongLab/LabHorizon-Model") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 9371e9d9d5b75a5a32d16c0d9d4dad1630b143322aecdaf056b7fa6b25aa0e36
- Size of remote file:
- 1.28 MB
- SHA256:
- 2153bf1bb6b1ae1a2f7d2f8394a15e2a23685b97b4763254ea0fc1c816d8053d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.