Instructions to use kromcomp/L3.1-Control-r64-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kromcomp/L3.1-Control-r64-LoRA with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kromcomp/L3.1-Control-r64-LoRA", dtype="auto") - PEFT
How to use kromcomp/L3.1-Control-r64-LoRA with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Control-r64-LoRA
This is a LoRA extracted from a language model. It was extracted using mergekit.
LoRA Details
This LoRA adapter was extracted from Delta-Vector/Control-8B-V1.1 and uses arcee-ai/Llama-3.1-SuperNova-Lite as a base.
Parameters
The following command was used to extract this LoRA adapter:
mergekit-extract-lora Delta-Vector/Control-8B-V1.1 arcee-ai/Llama-3.1-SuperNova-Lite OUTPUT_PATH --no-lazy-unpickle --skip-undecomposable --rank=64 --extend-vocab --model_name=Control-r64-LoRA --verbose
Inference Providers NEW
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Model tree for kromcomp/L3.1-Control-r64-LoRA
Base model
Delta-Vector/Control-8B-V1.1
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kromcomp/L3.1-Control-r64-LoRA", dtype="auto")