Instructions to use lucifertrj/panda_coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lucifertrj/panda_coder with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("AIDC-ai-business/Luban-13B") model = PeftModel.from_pretrained(base_model, "lucifertrj/panda_coder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13fc19c197ebd2ef184606066970c0b397ff85e53242466f2f3d2c7e6656f4fd
- Size of remote file:
- 210 MB
- SHA256:
- c1b1266c3b801a7608bdd27ab80afd6321e4fe9ffa4eeb1a2bd151a2ff34bbdf
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