Instructions to use shadyy/RDMM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shadyy/RDMM with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("astronomer/Llama-3-8B-Instruct-GPTQ-4-Bit") model = PeftModel.from_pretrained(base_model, "shadyy/RDMM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07bc01e5fbd503df3063f7fc79cd4f7440d08de2b78b2ceb185159f36e7db0c0
- Size of remote file:
- 2.68 GB
- SHA256:
- a99b0e6e549476449ef8c5db4ed98db8092bb90559ba4fe28e92eec2d53f0c10
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