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README.md
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@@ -21,6 +21,14 @@ Designed for **low-latency inference** on **NVIDIA RTX GPUs**, leveraging:
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FlashHead matches the gemma-3-1b-it baseline within rounding error on common benchmarks (MMLU-Pro, HellaSwag, GSM8K, etc.) and, combined with quantization, delivers SOTA on-device latency.
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---
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## Model Details
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FlashHead matches the gemma-3-1b-it baseline within rounding error on common benchmarks (MMLU-Pro, HellaSwag, GSM8K, etc.) and, combined with quantization, delivers SOTA on-device latency.
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### Quickstart
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Launch a chat window with commands for /reset and /exit with
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```shell
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pip install embedl-models
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python3 -m embedl.models.vllm.demo --model embedl/gemma-3-1b-it-FlashHead
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```
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---
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## Model Details
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