Instructions to use qingy2024/T2-3B-Checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use qingy2024/T2-3B-Checkpoint with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("InfiniAILab/OpenR1-Qwen-3B-SFT-Instruct") model = PeftModel.from_pretrained(base_model, "qingy2024/T2-3B-Checkpoint") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from qingy2024/T2-3B-Checkpoint: direct link, hf CLI and curl.
- Browser
- Download file 245 MB
-
https://huggingface.co/qingy2024/T2-3B-Checkpoint/resolve/main/optimizer.pt
- Command line
-
hf download hf://qingy2024/T2-3B-Checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/qingy2024/T2-3B-Checkpoint/resolve/main/optimizer.pt
245 MB
- Xet hash:
- eb8224ba0c554ab6e34ce836891c5ad08c40e2bbc3a6abd2e6d2e57786215797
- Size of remote file:
- 245 MB
- SHA256:
- ac998e1563beef6662160cf16512dfa25fbf99df69d5a028b3632edb2e9a02c6
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