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:
- f88a4fb2a218c42a1abbd9f2bd305955935c62684e22e17cec21eb696e358573
- Size of remote file:
- 6.78 kB
- SHA256:
- e60231912c9111d3b6f2f012e6e0ed13b38bcbe4fbf62b9a74ba0ba9f36e7308
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