Instructions to use mamung/2c15f6fc-8832-491b-bb73-ac4775664582 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mamung/2c15f6fc-8832-491b-bb73-ac4775664582 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama") model = PeftModel.from_pretrained(base_model, "mamung/2c15f6fc-8832-491b-bb73-ac4775664582") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d45e287c18895199aa0d34226c7fa7f990d98e5160ff3095b60582bfa9cc98e
- Size of remote file:
- 101 MB
- SHA256:
- eb77c099d494f2cc1e4c03964f43740d07abc45295f7553fb5b587b64eaea4ec
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.