Instructions to use Sorour/cls_sentiment_llama3_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Sorour/cls_sentiment_llama3_v3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct") model = PeftModel.from_pretrained(base_model, "Sorour/cls_sentiment_llama3_v3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6c52e3061cea68137cb65d20f38fbb0cf69abff9a1328383565b300b44b81f4
- Size of remote file:
- 5.11 kB
- SHA256:
- 5d9fbb2d01f97284dd8f59bb84cdbff4a4bd4eb38acf3d84e208e25bd13174e9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.