State-of-the-arts General LLMs - based on Qwen1.5 • 20 items • Updated • 12
Quyen
👁 QuyenModel Description
Quyen is our first flagship LLM series based on the Qwen1.5 family. We introduced 6 different versions:
- Quyen-SE (0.5B)
- Quyen-Mini (1.8B)
- Quyen (4B)
- Quyen-Plus (7B)
- Quyen-Pro (14B)
- Quyen-Pro-Max (72B)
All models were trained with SFT and DPO using the following dataset:
- OpenHermes-2.5 by Teknium
- Capyabara by LDJ
- argilla/distilabel-capybara-dpo-7k-binarized by argilla
- orca_dpo_pairs by Intel
- and Private Data by Ontocord & BEE-spoke-data
Prompt Template
- All Quyen models use ChatML as the default template:
<|im_start|>system
You are a sentient, superintelligent artificial general intelligence, here to teach and assist me.<|im_end|>
<|im_start|>user
Hello world.<|im_end|>
<|im_start|>assistant
- You can also use
apply_chat_template:
messages = [
{"role": "system", "content": "You are a sentient, superintelligent artificial general intelligence, here to teach and assist me."},
{"role": "user", "content": "Hello world."}
]
gen_input = tokenizer.apply_chat_template(message, return_tensors="pt")
model.generate(**gen_input)
Benchmarks:
- Coming Soon! We will update the benchmarks later
Acknowledgement
- We're incredibly grateful to Tensoic and Ontocord for their generous support with compute and data preparation.
- Special thanks to the Qwen team for letting us access the models early for these amazing finetunes.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 46.14 |
| AI2 Reasoning Challenge (25-Shot) | 39.33 |
| HellaSwag (10-Shot) | 60.57 |
| MMLU (5-Shot) | 43.93 |
| TruthfulQA (0-shot) | 46.44 |
| Winogrande (5-shot) | 59.12 |
| GSM8k (5-shot) | 27.45 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard39.330
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard60.570
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard43.930
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard46.440
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard59.120
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard27.450
