Instructions to use dada22231/1b8ab1e0-6218-4b84-9c24-f74892620058 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/1b8ab1e0-6218-4b84-9c24-f74892620058 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-1.5B") model = PeftModel.from_pretrained(base_model, "dada22231/1b8ab1e0-6218-4b84-9c24-f74892620058") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc25d03b0040834e7b90f42019f54ea0b14e28fe3229ec72ac63894c9158fe12
- Size of remote file:
- 15 kB
- SHA256:
- dbd9c2ca12fd6d73447f9642f500ea8b2673851b6c1c90b62bcf0d968860c993
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