---
library_name: transformers
license: mit
---

# sglang-EAGLE3-Llama-4-Scout-17B-16E-Instruct-v1

## Model Introduction
The Eagle3 draft model was trained using the [SpecForge](https://github.com/sgl-project/SpecForge) framework for the Llama4 Scout 17B-16E Instruct model, leveraging a combination of UltraChat and ShareGPT datasets. Under a 3-1-4 speculative decoding configuration—3 speculative steps, top-1 token selection, and 4 draft tokens—it achieves an acceptance length of 2.27.

## Usage
You can use this Eagle3 draft model in [SGLang](https://github.com/sgl-project/sglang) with the following command:

```bash
python3 -m sglang.launch_server \
    --model meta-llama/Llama-4-Scout-17B-16E-Instruct  \
    --speculative-algorithm EAGLE3 \
    --speculative-draft-model-path lmsys/sglang-EAGLE3-Llama-4-Scout-17B-16E-Instruct-v1 \
    --speculative-num-steps 3 \
    --speculative-eagle-topk 1 \
    --speculative-num-draft-tokens 4 \
    --mem-fraction-static 0.75 \
    --cuda-graph-max-bs 2 \
    --tp 8 \
    --context-length 8192 \
    --trust-remote-code \
    --host 0.0.0.0 \
    --port 30000 \
    --dtype bfloat16
```