Instructions to use jerseyjerry/Qwen-Qwen2-1.5B-Instruct-1725768009 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jerseyjerry/Qwen-Qwen2-1.5B-Instruct-1725768009 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "jerseyjerry/Qwen-Qwen2-1.5B-Instruct-1725768009") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 83e9c371565c4681fe53d7f2bbb71e277d4bdb46a2427f0c4d110c4218a35a56
- Size of remote file:
- 5.37 kB
- SHA256:
- e58c23ab0b1b979ad629dbea1b1ad6110e15c43294fff967b9f2d5a0a744c049
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.