Instructions to use arbinMichael/30stepphi35lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use arbinMichael/30stepphi35lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/phi-3.5-mini-instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "arbinMichael/30stepphi35lora") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from arbinMichael/30stepphi35lora: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/arbinMichael/30stepphi35lora/resolve/main/training_args.bin
- Command line
-
hf download hf://arbinMichael/30stepphi35lora/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/arbinMichael/30stepphi35lora/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- f2a3965a84247664dd08e26bf0554ec91851bfb0a121fae0ae13a93206bc79ce
- Size of remote file:
- 5.11 kB
- SHA256:
- 5124a6a274b65721ef12f3fb0ba621de5af0657ba8424ccb99d88333c702ce89
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.