Instructions to use tarabukinivan/0a68d25b-d86b-42a5-93e9-49451351341f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/0a68d25b-d86b-42a5-93e9-49451351341f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama") model = PeftModel.from_pretrained(base_model, "tarabukinivan/0a68d25b-d86b-42a5-93e9-49451351341f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a58f9185be8a8b5e0ee1e037f00ea2cf8cfdcf12b48a6ee28667c2581837429
- Size of remote file:
- 101 MB
- SHA256:
- eb3492c89a0d29769cfc811b7fdab797b8dd80bf6f606e5540884e2ba8bef5b3
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