Instructions to use Delta-Vector/Pascal-Base-Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Delta-Vector/Pascal-Base-Lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-3-12b-it") model = PeftModel.from_pretrained(base_model, "Delta-Vector/Pascal-Base-Lora") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from Delta-Vector/Pascal-Base-Lora: direct link, hf CLI and curl.
- Browser
- Download file 5.26 GB
-
https://huggingface.co/Delta-Vector/Pascal-Base-Lora/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://Delta-Vector/Pascal-Base-Lora/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/Delta-Vector/Pascal-Base-Lora/resolve/main/adapter_model.safetensors
5.26 GB
- Xet hash:
- 95ac186ca4535c69e54a9ecc0fcec7bc5fdf4300167b61bcc039ce71bec6123a
- Size of remote file:
- 5.26 GB
- SHA256:
- ed551bf6e7b15aa3624c4bd99e7376e07a0a9abd7ef220e492940e68fd781690
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