Instructions to use anthonymeo/LLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use anthonymeo/LLM with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("internlm/internlm2_5-7b-chat") model = PeftModel.from_pretrained(base_model, "anthonymeo/LLM") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from anthonymeo/LLM: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/anthonymeo/LLM/resolve/main/training_args.bin
- Command line
-
hf download hf://anthonymeo/LLM/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/anthonymeo/LLM/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 105fa9bc17fd94a46574e984280cabaca6fcb9c328efc87e7628ab6134fa61e4
- Size of remote file:
- 5.3 kB
- SHA256:
- 28a84bb19d0747e5e32709d720a3932cbdf61dc13a8bc483f6470afbfc08189f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.