Instructions to use thangla01/521bcd67-9ca7-4f94-b0c3-b0b4f64e2a8e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thangla01/521bcd67-9ca7-4f94-b0c3-b0b4f64e2a8e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmsys/vicuna-7b-v1.5") model = PeftModel.from_pretrained(base_model, "thangla01/521bcd67-9ca7-4f94-b0c3-b0b4f64e2a8e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f9b49b0f93092e74afd2c0ea66c36290652797b378cec679cc69309e9a9107f
- Size of remote file:
- 80.1 MB
- SHA256:
- 5d076486091fc75e31f25e9886280c4612efa0898c085de50acc6f60fb0f3128
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