sgl-project/SpecForge

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1145 stars · 324 forks observed · 2026-09-03

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SpecForge is a Python framework from the SGLang team for training speculative decoding models such as EAGLE/EAGLE3 draft heads. Trained models port directly to SGLang serving to accelerate LLM inference.

Use cases

• train an EAGLE3 speculative decoding head for a Llama model
• speed up LLM inference with speculative decoding in SGLang
• run distributed draft model training with FSDP
• train speculative decoding models on AMD ROCm or Ascend NPUs
• prepare datasets for speculative decoding training

When to choose

• you serve LLMs with SGLang and want faster decoding via speculative decoding
• you need a maintained, out-of-the-box speculative decoding training pipeline
• you want disaggregated or colocated training with parallel topologies

When to avoid

• you serve models with frameworks other than SGLang
• you need general-purpose LLM fine-tuning rather than speculative decoding draft models
• you have no multi-GPU hardware for training

Facets

framework · maturity active

llm-training machine-learning gpu-computing large-language-models deep-learning machine-learning developer-tools python speculative-decoding eagle3 sglang pytorch fsdp distributed-training llm-inference-acceleration gpu linux docker

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markdown · JSON · MCP: product_card(name="sgl-project/SpecForge")