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 tokenizer.json from qingy2024/T2-3B-Checkpoint: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/qingy2024/T2-3B-Checkpoint/resolve/main/tokenizer.json
- Command line
-
hf download hf://qingy2024/T2-3B-Checkpoint/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/qingy2024/T2-3B-Checkpoint/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 855eda6fb6d66b1fb4ca72fc2c603490c08fe26eee221cf8d38c3f6a6541c0f6
- Size of remote file:
- 11.4 MB
- SHA256:
- 64e71213db910f5cafa86d35091f37393dcc344b1bbc34091d1b3eed4cca01d5
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