Instructions to use Infernaught/phi_countdown_n100_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_n100_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_n100_mcl_256_quantized") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Infernaught/phi_countdown_n100_mcl_256_quantized: direct link, hf CLI and curl.
- Browser
- Download file 6.26 kB
-
https://huggingface.co/Infernaught/phi_countdown_n100_mcl_256_quantized/resolve/bc7c8538e289d3e4ee83e972ca7b79b010a6734f/training_args.bin
- Command line
-
hf download hf://Infernaught/phi_countdown_n100_mcl_256_quantized@bc7c8538e289d3e4ee83e972ca7b79b010a6734f/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Infernaught/phi_countdown_n100_mcl_256_quantized/resolve/bc7c8538e289d3e4ee83e972ca7b79b010a6734f/training_args.bin
6.26 kB
- Xet hash:
- 6235ff6be8fd6bdeb45e4f8c93c113ec23534b8ce4b682502fef9aee6f4c5821
- Size of remote file:
- 6.26 kB
- SHA256:
- 0f6e4397e817d0c7f4721a08637703c7bf345deaf7e0f47a3f855d5468149434
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