Instructions to use adammandic87/c06f29f0-040d-4bbd-a3c6-dde510138739 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adammandic87/c06f29f0-040d-4bbd-a3c6-dde510138739 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Intel/neural-chat-7b-v3-3") model = PeftModel.from_pretrained(base_model, "adammandic87/c06f29f0-040d-4bbd-a3c6-dde510138739") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from adammandic87/c06f29f0-040d-4bbd-a3c6-dde510138739: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/adammandic87/c06f29f0-040d-4bbd-a3c6-dde510138739/resolve/main/adapter_model.bin
- Command line
-
hf download hf://adammandic87/c06f29f0-040d-4bbd-a3c6-dde510138739/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/adammandic87/c06f29f0-040d-4bbd-a3c6-dde510138739/resolve/main/adapter_model.bin
84 MB
- Xet hash:
- c93801e0a71a4a85f2978084412f0f7b250e98dea45024d4c47f42f908cbdadd
- Size of remote file:
- 84 MB
- SHA256:
- 674ad7fa5d3c34b45e5c02df58d6f77d6ddb1568d66ebad741cf7f51c9875ec6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.