63 lines
1.7 KiB
Markdown
63 lines
1.7 KiB
Markdown
---
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library_name: transformers
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license: other
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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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language:
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- en
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pipeline_tag: text-generation
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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. |