| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
|---|---|---|---|---|---|
| mlabonne/OmniTruthyBeagle-7B-v0 📄 | 57.8 | 45.72 | 77.49 | 76.16 | 50.18 |
| mlabonne/NeuralOmniBeagle-7B-v2 📄 | 57.75 | 45.86 | 77.31 | 75.34 | 50.09 |
| mlabonne/OmniBeagle-7B 📄 | 57.72 | 45.64 | 77.48 | 75.03 | 50.03 |
| mlabonne/NeuralOmniBeagle-7B 📄 | 57.71 | 45.85 | 77.26 | 76.06 | 50.03 |
| mlabonne/NeuralOmni-7B [📄](https://gist.github.com/mlabonne/4b5ecee86d0fd3714ba0cbd |
Maxime Labonne mlabonne
mlabonne
/ YALL - Yet Another LLM Leaderboard.md
Last active
May 28, 2024 12:52
Leaderboard made with 🧐 LLM AutoEval (https://github.com/mlabonne/llm-autoeval) using Nous benchmark suite.
mlabonne
/ merge_peft.py
Last active
May 6, 2024 16:20
Merge base model and peft adapter and push it to HF hub
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| # Example usage: | |
| # python merge_peft.py --base_model=meta-llama/Llama-2-7b-hf --peft_model=./qlora-out --hub_id=alpaca-qlora | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| from peft import PeftModel | |
| import torch | |
| import argparse | |
| def get_args(): |