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:
- 61aac6d40760e9c5170d92a1f3ff0636b4fc6a3d747b834482c3757f4903067a
- Size of remote file:
- 15 kB
- SHA256:
- 3391ab0ba6e2744970ade8b0dcdc0579f6b5e005857c636cb7ea76dc85d48f04
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