Speculators: Accelerate LLM Inference with Speculative Decoding
From the repo · “A unified library for building, evaluating, and storing speculative decoding algorithms for LLM inference in vLLM”
Speculators provides a unified library for building, evaluating, and storing speculative decoding algorithms for Large Language Model (LLM) inference
- •When you need to optimize LLM inference for your startup's natural language processing tasks
- •When you want to compare and evaluate different decoding algorithms for your LLM models
- •When you need to store and manage multiple speculative decoding algorithms for different LLM models
python examples/example.py --model_name-or-path vllm/lm_base --decoder topk --topk 5
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/speculators && curl -fsSL https://workflowstacks.com/api/skills/speculators/claude-skill -o ~/.claude/skills/speculators/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/speculators && curl -fsSL https://workflowstacks.com/api/skills/speculators/claude-skill -o ~/.claude/skills/speculators/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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