Open-Orca/OpenOrca
Viewer • Updated • 2.94M • 42.8k • 1.54k
How to use Andron00e/YetAnother_Open-Llama-3B-LoRA-OpenOrca with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="Andron00e/YetAnother_Open-Llama-3B-LoRA-OpenOrca") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Andron00e/YetAnother_Open-Llama-3B-LoRA-OpenOrca")
model = AutoModelForCausalLM.from_pretrained("Andron00e/YetAnother_Open-Llama-3B-LoRA-OpenOrca")https://huggingface.co/datasets/Open-Orca/OpenOrca
Evaluation of the model was carried out using EulerAI library, more precisely
hellaswag testing dataset
Accuracy
| Task | Version | Metric | Value | Stderr | |
|---|---|---|---|---|---|
| hellaswag | 0 | acc | 0.4899 | ± | 0.0050 |
| acc_norm | 0.6506 | ± | 0.0048 |
@software{openlm2023openllama,
author = {Geng, Xinyang and Liu, Hao},
title = {OpenLLaMA: An Open Reproduction of LLaMA},
month = May,
year = 2023,
url = {https://github.com/openlm-research/open_llama}
}
@software{eval-harness,
author = {Gao, Leo and
Tow, Jonathan and
Biderman, Stella and
Black, Sid and
DiPofi, Anthony and
Foster, Charles and
Golding, Laurence and
Hsu, Jeffrey and
McDonell, Kyle and
Muennighoff, Niklas and
Phang, Jason and
Reynolds, Laria and
Tang, Eric and
Thite, Anish and
Wang, Ben and
Wang, Kevin and
Zou, Andy},
title = {A framework for few-shot language model evaluation},
month = sep,
year = 2021,
publisher = {Zenodo},
version = {v0.0.1},
doi = {10.5281/zenodo.5371628},
url = {https://doi.org/10.5281/zenodo.5371628}
}