Instructions to use prxy5608/d438699a-0dd6-4b02-8f3f-237b7cfea0e0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5608/d438699a-0dd6-4b02-8f3f-237b7cfea0e0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-360M") model = PeftModel.from_pretrained(base_model, "prxy5608/d438699a-0dd6-4b02-8f3f-237b7cfea0e0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 460c4aa755a44ff571e26867a818c8d56af616b60627f807329dc41fae826a9c
- Size of remote file:
- 6.84 kB
- SHA256:
- 5734909b99cd7e6e33a5556312d2dce2bea98cb1eadcaefbb42c808c32cb5f6f
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