Instructions to use Jnx03/kanitakorn-260614-glm4-glm4-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Jnx03/kanitakorn-260614-glm4-glm4-final 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-final") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce9cbc186a695adebe8584e82ce593c487f052c0ee124ef2f7dd28ed1c924c7b
- Size of remote file:
- 20 MB
- SHA256:
- 76ebeac0d8bd7879ead7b43c16b44981f277e47225de2bd7de9ae1a6cc664a8c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.