Instructions to use avinot/LoLlama3.2-1B-lora-50ep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use avinot/LoLlama3.2-1B-lora-50ep 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, "avinot/LoLlama3.2-1B-lora-50ep") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from avinot/LoLlama3.2-1B-lora-50ep: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/avinot/LoLlama3.2-1B-lora-50ep/resolve/main/training_args.bin
- Command line
-
hf download hf://avinot/LoLlama3.2-1B-lora-50ep/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/avinot/LoLlama3.2-1B-lora-50ep/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 3d3eaa5b0cb0e200f0cbc3a3c55164d0f54cf83ead214393a4e4fcb660bc699b
- Size of remote file:
- 5.37 kB
- SHA256:
- 0592c0a7a53c2fd16965819afbedf8ffffdeecb2563d6725cdf3fccded7a157d
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