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:
- 8bd8da7f720f1b86c20d3f291b8350dcec06ffb8b5e80473196f95c04193995b
- Size of remote file:
- 6.84 kB
- SHA256:
- e7df0cc160856fca13241deae2a453b990a272f43eaccf49ee0bee150fb93ff6
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