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Jonna Matthiesen
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⚡ FlashHead: Fast LM Head Inference - Now a Simple vLLM Plugin
flash-head replaces the dense LM head with a two-stage retrieval pipeline - up to 2x inference speedup, training-free. Previously required custom Docker images; now it's just:
```
pip install flash-head
vllm serve embedl/Qwen3-1.7B-FlashHead-W4A16
```
✨ The plugin activates automatically via vLLM's `vllm.general_plugins` entry point. No source patches, no custom imports.
🧩 Supported models (full collection): https://huggingface.co/Qwen Qwen3, https://huggingface.co/meta-llama Llama3, https://huggingface.co/google Gemma3, https://huggingface.co/nvidia Cosmos-Reason2 - BF16 and W4A16 variants.
https://huggingface.co/collections/embedl/flashhead
📊 https://huggingface.co/spaces/embedl/Edge-Inference-Benchmarks
🔧 Benchmark it yourself:
```
vllm bench latency --model embedl/Qwen3-1.7B-FlashHead-W4A16 --batch-size 1
# Baseline comparison
FLASHHEAD_ENABLED=0 vllm bench latency --model embedl/Qwen3-1.7B-FlashHead-W4A16 --batch-size 1
```
FlashHead shines at low batch sizes; the typical real-time / on-device use case. 🚀 new activity 2 days ago
embedl/Qwen3-0.6B-FlashHead:vllm serve updated a Space 3 days ago
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FlashHead: Accelerating Language Model Inference ~ *Efficient drop-in replacement for the classification head*
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