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:
- edd5b3942d9ffaa3f5d4df87612f3d627bf01ff8f347d2b887bb8a99da09b9a4
- Size of remote file:
- 80.8 MB
- SHA256:
- a10d8ee8cd4ef5b19f56eb1d3e44b5313d6630724710729da9d7a25d6fba1d21
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.