Instructions to use socius/Llama-Centaur-8B-LoRA-r4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use socius/Llama-Centaur-8B-LoRA-r4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "socius/Llama-Centaur-8B-LoRA-r4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download training_args.bin from socius/Llama-Centaur-8B-LoRA-r4: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/socius/Llama-Centaur-8B-LoRA-r4/resolve/main/training_args.bin
- Command line
-
hf download hf://socius/Llama-Centaur-8B-LoRA-r4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/socius/Llama-Centaur-8B-LoRA-r4/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 99da1fbe6480daeb6b05f6f2a9b06af62f3a3eecc70ab759a638d38ee71d09f5
- Size of remote file:
- 5.84 kB
- SHA256:
- de8e15053b2c4eba61e319218b45896103174b917f3a43201d08002e72b7bc27
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