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Model: vilm/Quyen-Mini-v0.1 Source: Original Platform
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README.md
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README.md
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---
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language:
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- en
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license: other
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library_name: transformers
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datasets:
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- teknium/OpenHermes-2.5
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- LDJnr/Capybara
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- Intel/orca_dpo_pairs
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- argilla/distilabel-capybara-dpo-7k-binarized
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pipeline_tag: text-generation
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model-index:
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- name: Quyen-Mini-v0.1
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 39.33
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 60.57
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 43.93
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 46.44
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 59.12
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 27.45
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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---
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# Quyen
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<img src="quyen.webp" width="512" height="512" alt="Quyen">
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# Model Description
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Quyen is our first flagship LLM series based on the Qwen1.5 family. We introduced 6 different versions:
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- **Quyen-SE (0.5B)**
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- **Quyen-Mini (1.8B)**
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- **Quyen (4B)**
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- **Quyen-Plus (7B)**
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- **Quyen-Pro (14B)**
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- **Quyen-Pro-Max (72B)**
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All models were trained with SFT and DPO using the following dataset:
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- *OpenHermes-2.5* by **Teknium**
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- *Capyabara* by **LDJ**
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- *argilla/distilabel-capybara-dpo-7k-binarized* by **argilla**
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- *orca_dpo_pairs* by **Intel**
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- and Private Data by **Ontocord** & **BEE-spoke-data**
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# Prompt Template
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- All Quyen models use ChatML as the default template:
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```
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<|im_start|>system
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You are a sentient, superintelligent artificial general intelligence, here to teach and assist me.<|im_end|>
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<|im_start|>user
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Hello world.<|im_end|>
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<|im_start|>assistant
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```
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- You can also use `apply_chat_template`:
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```python
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messages = [
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{"role": "system", "content": "You are a sentient, superintelligent artificial general intelligence, here to teach and assist me."},
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{"role": "user", "content": "Hello world."}
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]
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gen_input = tokenizer.apply_chat_template(message, return_tensors="pt")
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model.generate(**gen_input)
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```
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# Benchmarks:
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- Coming Soon! We will update the benchmarks later
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# Acknowledgement
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- We're incredibly grateful to **Tensoic** and **Ontocord** for their generous support with compute and data preparation.
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- Special thanks to the Qwen team for letting us access the models early for these amazing finetunes.
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_vilm__Quyen-Mini-v0.1)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |46.14|
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|AI2 Reasoning Challenge (25-Shot)|39.33|
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|HellaSwag (10-Shot) |60.57|
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|MMLU (5-Shot) |43.93|
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|TruthfulQA (0-shot) |46.44|
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|Winogrande (5-shot) |59.12|
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|GSM8k (5-shot) |27.45|
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