Instructions to use bane5631/194c9c27-ed1a-4418-a8c0-b13eafff85bd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bane5631/194c9c27-ed1a-4418-a8c0-b13eafff85bd with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Korabbit/llama-2-ko-7b") model = PeftModel.from_pretrained(base_model, "bane5631/194c9c27-ed1a-4418-a8c0-b13eafff85bd") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from bane5631/194c9c27-ed1a-4418-a8c0-b13eafff85bd: direct link, hf CLI and curl.
- Browser
- Download file 80.1 MB
-
https://huggingface.co/bane5631/194c9c27-ed1a-4418-a8c0-b13eafff85bd/resolve/main/adapter_model.bin
- Command line
-
hf download hf://bane5631/194c9c27-ed1a-4418-a8c0-b13eafff85bd/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/bane5631/194c9c27-ed1a-4418-a8c0-b13eafff85bd/resolve/main/adapter_model.bin
80.1 MB
- Xet hash:
- 39ab2de3e567b6140498e3882e9f8f73904cbd9fdeba0c6f0450be751c817edd
- Size of remote file:
- 80.1 MB
- SHA256:
- e5a10d83fd0d6edf94f8e6c44948dc4329c08ba98955c6122e9de8dec6cdfb25
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.