Instructions to use strumber/Llama2letsmod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use strumber/Llama2letsmod with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "strumber/Llama2letsmod") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-300/training_args.bin from strumber/Llama2letsmod: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/strumber/Llama2letsmod/resolve/main/checkpoint-300/training_args.bin
- Command line
-
hf download hf://strumber/Llama2letsmod/checkpoint-300/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/strumber/Llama2letsmod/resolve/main/checkpoint-300/training_args.bin
4.03 kB
- Xet hash:
- fcd85ba2992550f17052816811e16c7c5b4e2b65729ce690453dbc4c0249492e
- Size of remote file:
- 4.03 kB
- SHA256:
- d31fd82befd9ee5457878ffc81e0e912118afde0e205cd756d8f332797f78b00
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