Instructions to use nblinh63/8189c395-755b-4ff5-b530-680761946b43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh63/8189c395-755b-4ff5-b530-680761946b43 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-360M-Instruct") model = PeftModel.from_pretrained(base_model, "nblinh63/8189c395-755b-4ff5-b530-680761946b43") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74af22ff93e48c1943749424502b62a000f8f214b759afffc6557101bb7fa968
- Size of remote file:
- 17.4 MB
- SHA256:
- 217581303f84e8bab116c4ffae3b06f304b2c40e1f62520dc5451227af4a8311
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