🌟⚛ 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
🧑🏫 Benchmark
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🔍 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.
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Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| 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 |
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Dataset used to train raincandy-u/Quark-464M-v0.1.alpha
Space using raincandy-u/Quark-464M-v0.1.alpha 1
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard31.400
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard47.310
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard34.550
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard41.840
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard55.170
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard3.790