Instructions to use pattonma/llama381binstruct_summarize_short with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use pattonma/llama381binstruct_summarize_short with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "pattonma/llama381binstruct_summarize_short") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pattonma/llama381binstruct_summarize_short: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/pattonma/llama381binstruct_summarize_short/resolve/main/training_args.bin
- Command line
-
hf download hf://pattonma/llama381binstruct_summarize_short/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pattonma/llama381binstruct_summarize_short/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 6f0b06314cd2e22e7b8cccca9c37d82253ef2577fa171da233b8a68ad808ca89
- Size of remote file:
- 5.5 kB
- SHA256:
- 85a675f93aa23b6ea7787b25d7d64bb45e0eda35ae6c9d9ec6861b0dc854ab7d
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