Instructions to use dada22231/0ce63847-2fb3-4975-a47e-f3f32ee8b49a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/0ce63847-2fb3-4975-a47e-f3f32ee8b49a 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, "dada22231/0ce63847-2fb3-4975-a47e-f3f32ee8b49a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08e8d314b7563826d146488d06a4cfab154e271d91f52127e3aed6912a59d942
- Size of remote file:
- 15 kB
- SHA256:
- cd289090f6d74e2e999c7929f0fd9065fda4b3490b1de0f8ade7a58d34f0936b
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