Instructions to use diffusion-reasoning/d1_SFT_us_countdown-4000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use diffusion-reasoning/d1_SFT_us_countdown-4000 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("GSAI-ML/LLaDA-8B-Instruct") model = PeftModel.from_pretrained(base_model, "diffusion-reasoning/d1_SFT_us_countdown-4000") - Notebooks
- Google Colab
- Kaggle
Download rng_state_2.pth from diffusion-reasoning/d1_SFT_us_countdown-4000: direct link, hf CLI and curl.
- Browser
- Download file 15 kB
-
https://huggingface.co/diffusion-reasoning/d1_SFT_us_countdown-4000/resolve/main/rng_state_2.pth
- Command line
-
hf download hf://diffusion-reasoning/d1_SFT_us_countdown-4000/rng_state_2.pth
-
curl -L -o rng_state_2.pth https://huggingface.co/diffusion-reasoning/d1_SFT_us_countdown-4000/resolve/main/rng_state_2.pth
15 kB
- Xet hash:
- f1a4b82770a3af0bf5d31029cef18341e241ff2d5aeb9d5e7b0ac4fc1be32f76
- Size of remote file:
- 15 kB
- SHA256:
- 5c9dd5ce85358095bd9d1dafa07f574c60e0e7d8e05f5d6b8afa3f0b8a789ec4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.