Instructions to use Infernaught/phi_countdown_n50_mcl_256_quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Infernaught/phi_countdown_n50_mcl_256_quantized with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3.5-mini-instruct") model = PeftModel.from_pretrained(base_model, "Infernaught/phi_countdown_n50_mcl_256_quantized") - Notebooks
- Google Colab
- Kaggle
Download scheduler.pt from Infernaught/phi_countdown_n50_mcl_256_quantized: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/Infernaught/phi_countdown_n50_mcl_256_quantized/resolve/62d1f6176286b4dcedef99eabea1cb7a2bd64b6c/scheduler.pt
- Command line
-
hf download hf://Infernaught/phi_countdown_n50_mcl_256_quantized@62d1f6176286b4dcedef99eabea1cb7a2bd64b6c/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/Infernaught/phi_countdown_n50_mcl_256_quantized/resolve/62d1f6176286b4dcedef99eabea1cb7a2bd64b6c/scheduler.pt
1.06 kB
- Xet hash:
- 9394bf01621b0bda05e17ea55f64afcd6f73ad547bc2dddcbb20c8a3627bb860
- Size of remote file:
- 1.06 kB
- SHA256:
- b6bd15293c66dffae3d7549c72be051599953caeb2059c4034a302a15619af72
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.