Instructions to use ulas742/lora-mid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ulas742/lora-mid with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "ulas742/lora-mid") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ulas742/lora-mid: direct link, hf CLI and curl.
- Browser
- Download file 5.71 kB
-
https://huggingface.co/ulas742/lora-mid/resolve/main/training_args.bin
- Command line
-
hf download hf://ulas742/lora-mid/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ulas742/lora-mid/resolve/main/training_args.bin
5.71 kB
- Xet hash:
- 072abc3fbce51879fadd44af84e833df085b305111e37441dbb6f27e4071a34b
- Size of remote file:
- 5.71 kB
- SHA256:
- daadbf7c74f31ef9cab10f6fb8d82f79520c3bd43f7dee1b2d4f48eb81284b60
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