Instructions to use Jnx03/kanitakorn-260614-glm4-glm4-step160 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Jnx03/kanitakorn-260614-glm4-glm4-step160 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("zai-org/GLM-4-9B-0414") model = PeftModel.from_pretrained(base_model, "Jnx03/kanitakorn-260614-glm4-glm4-step160") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ee4bd58225960ebf2706c4e0406f1f0f6fe562e5fb95d95c31bd092e5f49c2b
- Size of remote file:
- 5.65 kB
- SHA256:
- 604698582effaf6fa275bf04f115e31759337d158ee3332f020c3eec975b676a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.