Instructions to use vdpappu/lora_coding_assistant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vdpappu/lora_coding_assistant with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b") model = PeftModel.from_pretrained(base_model, "vdpappu/lora_coding_assistant") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3e91bde2dfe6b502d18049247e25cc8138af5c7b46ce302e5060caa1ce7f225
- Size of remote file:
- 3.7 MB
- SHA256:
- 006ceb5faf562c3dcd9eb043d0f21c10a50f4d1659b4c7511abc62575ea47dfa
路
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