Instructions to use dada22231/8e1125fa-262f-4c76-b23c-fb7b2fd6270e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/8e1125fa-262f-4c76-b23c-fb7b2fd6270e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "dada22231/8e1125fa-262f-4c76-b23c-fb7b2fd6270e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22db26aad50178469196f51d78799ddd5a9af018c1859cf94137ea75b09c743f
- Size of remote file:
- 6.84 kB
- SHA256:
- bf76e5737af6c63ccc2262b074d9d50e1aa8c0cfe01acfc1375dafc35c1fe1c6
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