en license: other library_name: transformers datasets:
teknium/OpenHermes-2.5
LDJnr/Capybara
Intel/orca_dpo_pairs
argilla/distilabel-capybara-dpo-7k-binarized pipeline_tag: text-generation model-index:
name: Quyen-Plus-v0.1 results:
- task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics:
  - type: acc_norm value: 55.72 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Plus-v0.1 name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics:
  - type: acc_norm value: 78.52 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Plus-v0.1 name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics:
  - type: acc value: 60.45 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Plus-v0.1 name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics:
  - type: mc2 value: 53.6 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Plus-v0.1 name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics:
  - type: acc value: 71.27 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Plus-v0.1 name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics:
  - type: acc value: 60.05 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Plus-v0.1 name: Open LLM Leaderboard

Quyen

Model 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:

python

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.	63.27
AI2 Reasoning Challenge (25-Shot)	55.72
HellaSwag (10-Shot)	78.52
MMLU (5-Shot)	60.45
TruthfulQA (0-shot)	53.60
Winogrande (5-shot)	71.27
GSM8k (5-shot)	60.05

RichardErkhov/vilm_-_Quyen-Plus-v0.1-4bits

Original model description: