Instructions to use mrhunghd/f1631a0d-ccd2-49c1-8dce-a7d76efe8270 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mrhunghd/f1631a0d-ccd2-49c1-8dce-a7d76efe8270 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "mrhunghd/f1631a0d-ccd2-49c1-8dce-a7d76efe8270") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 876128f167496a45ad59c2851d86de570b89f58fb18d5ff1b7fede2a844574f4
- Size of remote file:
- 80.9 MB
- SHA256:
- 1f92455a5d3db24bd72034c918d07669681303a2c9ad77a4ee23502ce531005e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.