Quyen-Pro-v0.1-GPTQ / README.md
LoneStriker's picture
Upload folder using huggingface_hub
d91ec07 verified
|
raw
history blame
1.77 kB
metadata
library_name: transformers
license: other
datasets:
  - teknium/OpenHermes-2.5
  - LDJnr/Capybara
  - Intel/orca_dpo_pairs
  - argilla/distilabel-capybara-dpo-7k-binarized
language:
  - en
pipeline_tag: text-generation

Quyen

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:
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.