Image-Text-to-Text
PEFT
Safetensors
laboratory
protocol-conditioned-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:
- 514d6a5b0694e94cca9b7a783c1cb24ca34c14677d7c654e399b6a09aa30a6c0
- Size of remote file:
- 5.71 kB
- SHA256:
- 5228cdd5eb9358c1a0239811495149912109515f66a9f22386e040bdf16b1dd0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.