---
language:
- zh
- en
license: other
library_name: transformers
datasets:
- Open-Orca/OpenOrca
pipeline_tag: text-generation
license_name: tongyi-qianwen-research
license_link: https://huggingface.co/Qwen/Qwen1.5-32B/blob/main/LICENSE
model-index:
- name: Quark-464M-v0.1.alpha
  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: 31.4
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Quark-464M-v0.1.alpha
      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: 47.31
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Quark-464M-v0.1.alpha
      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: 34.55
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Quark-464M-v0.1.alpha
      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: 41.84
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Quark-464M-v0.1.alpha
      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: 55.17
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Quark-464M-v0.1.alpha
      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: 3.79
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Quark-464M-v0.1.alpha
      name: Open LLM Leaderboard
---

# 🌟⚛ Introducing Quark Series: Empowering Edge Devices with Swift Bilingual Conversational AI

Presenting Quark-620M-v0.1.alpha, the first model in our Quark series. 

Quark models focus on delivering exceptional English and Chinese conversational performance on edge devices with rapid inference speed.

# 🗨 Example

![image/png](https://cdn-uploads.huggingface.co/production/uploads/657eb5b256c9c67605a6e8b5/2720yGF0ERuz2DSr6HJLe.png)

# 🧑‍🏫 Benchmark

*⏳Wait for uploading*

# 🔍 Disclaimer
As an alpha preview release without RLHF fine-tuning, we do not take responsibility for potentially harmful responses and are committed to continuous improvement based on user feedback and research.

# 👥 Join [Our Discord community](https://discord.gg/ATfjwje3)!
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_raincandy-u__Quark-464M-v0.1.alpha)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |35.68|
|AI2 Reasoning Challenge (25-Shot)|31.40|
|HellaSwag (10-Shot)              |47.31|
|MMLU (5-Shot)                    |34.55|
|TruthfulQA (0-shot)              |41.84|
|Winogrande (5-shot)              |55.17|
|GSM8k (5-shot)                   | 3.79|