Instructions to use ToastyPigeon/a-glm-train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ToastyPigeon/a-glm-train with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("THUDM/GLM-4-32B-0414") model = PeftModel.from_pretrained(base_model, "ToastyPigeon/a-glm-train") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7388b6125af1bed2967c1ae2f5bac9e698e68f7bd1a6b09980d152cc224cd929
- Size of remote file:
- 520 MB
- SHA256:
- 5a466f86ba55f590c748d1bc349d5fe6c57546e91129c4c900d8113eb56637dd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.