Instructions to use lhong4759/b95f4cae-029d-49e0-ba80-f12e74daffa6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lhong4759/b95f4cae-029d-49e0-ba80-f12e74daffa6 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-3B") model = PeftModel.from_pretrained(base_model, "lhong4759/b95f4cae-029d-49e0-ba80-f12e74daffa6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8cdd50f7ce43a0fc496bd7f3bb36acdee58741cb10397624dd94986ce18e371
- Size of remote file:
- 6.78 kB
- SHA256:
- f89bfbbc3400b085d3c389570de172e572aecfc55a11ad8a33bbce3b23b2aee7
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