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‎README.md‎

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<div align="center">
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[![Build](https://github.com/Crynge/SpecInferKit/actions/workflows/ci.yml/badge.svg)](https://github.com/Crynge/SpecInferKit/actions/workflows/ci.yml)
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[![Python 3.11+](https://img.shields.io/badge/python-3.11%2B-blue)](https://python.org)
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[![License](https://img.shields.io/badge/license-MIT-green)](LICENSE)
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# ⚡ SpecInferKit
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# SpecInferKit
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**Production-grade speculative decoding for large language models** — accelerate LLM inference by **2–3×** without quality degradation using Eagle draft models, Medusa multi-token heads, and FP8 quantization.
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**Production-grade speculative decoding for large language models.**
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[![CI](https://img.shields.io/github/actions/workflow/status/Crynge/SpecInferKit/ci.yml?branch=main&label=CI&logo=github)](https://github.com/Crynge/SpecInferKit/actions/workflows/ci.yml)
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[![Python](https://img.shields.io/badge/python-3.11%2B-3776AB?logo=python)](https://python.org)
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[![License](https://img.shields.io/github/license/Crynge/SpecInferKit?color=blue)](LICENSE)
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[![Stars](https://img.shields.io/github/stars/Crynge/SpecInferKit?style=flat&logo=github)](https://github.com/Crynge/SpecInferKit)
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[![Last Commit](https://img.shields.io/github/last-commit/Crynge/SpecInferKit?logo=git)](https://github.com/Crynge/SpecInferKit/commits/main)
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[![Code Size](https://img.shields.io/github/languages/code-size/Crynge/SpecInferKit?logo=files)](https://github.com/Crynge/SpecInferKit)
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SpecInferKit accelerates LLM inference by predicting and verifying multiple future tokens in parallel, reducing latency by 2–3x without quality degradation.
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[Features](#features) • [Quick Start](#quick-start) • [Architecture](#architecture) • [Benchmarks](#benchmarks) • [Modules](#modules) • [Contributing](#contributing)
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---
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## Architecture
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> **⭐ Love SpecInferKit?** Star it on GitHub — it helps others discover the project!
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```
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┌──────────────────┐
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│ Input Prompt │
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└────────┬─────────┘
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│
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┌────────────────────┼────────────────────┐
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│ │ │
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┌────▼────┐ ┌─────▼─────┐ ┌────▼────┐
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│ Eagle │ │ Medusa │ │ Draft │
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│ Draft │ │ Head │ │ Model │
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│ Model │ │ Network │ │ (Ext.) │
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└────┬────┘ └─────┬─────┘ └────┬────┘
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│ │ │
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└────────────────────┼────────────────────┘
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│
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┌────────▼────────┐
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│ Verification │
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│ (Rejection │
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│ Sampling) │
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└────────┬────────┘
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│
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┌────────▼────────┐
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│ Output Text │
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└─────────────────┘
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```
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</div>
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---
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## Features
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| Capability | Description |
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|---|---|
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| **Eagle Drafting** | Autoregressive draft model with tree-based speculation |
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| **Medusa Heads** | Multi-token prediction via parallel feedforward heads |
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| **FP8 Quantization** | 8-bit floating point inference with minimal accuracy loss |
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| **Online Training** | Continuous fine-tuning of draft models during serving |
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| **Distributed Serving** | Multi-GPU speculative pipeline with load balancing |
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| **Extensible API** | Plugin interface for custom draft models and verifiers |
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| Capability | Description | Why It Matters |
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|---|---|---|
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| **Eagle Drafting** | Autoregressive draft model with **tree-based speculation** | 2.6× speedup on LLaMA-3.1-405B |
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| **Medusa Heads** | **Multi-token prediction** via parallel feedforward heads | Zero extra memory at inference |
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| **FP8 Quantization** | 8-bit float inference with **< 1% accuracy loss** | 2× memory reduction |
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| **Online Training** | Continuous **fine-tuning** of draft models during serving | Adapts to real-time traffic patterns |
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| **Distributed Serving** | Multi-GPU **speculative pipeline** with load balancing | Linear scaling with GPU count |
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| **Extensible API** | Plugin interface for **custom draft models** and verifiers | Bring your own architecture |
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---
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## Quick Start
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```bash
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# Install
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pip install specinferkit
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# Run with Eagle speculation
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specinferkit serve --model meta-llama/Llama-3.1-70B --draft eagle --draft-model draft-small
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# Run with Eagle speculation (LLaMA-3.1-70B + draft model)
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specinferkit serve \
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--model meta-llama/Llama-3.1-70B \
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--draft eagle \
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--draft-model draft-small
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# Run with Medusa heads
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specinferkit serve --model meta-llama/Llama-3.1-70B --draft medusa --medusa-heads 4
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specinferkit serve \
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--model meta-llama/Llama-3.1-70B \
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--draft medusa \
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--medusa-heads 4
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```
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```python
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from specinferkit import SpeculativeEngine
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engine = SpeculativeEngine(
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target_model="meta-llama/Llama-3.1-8B",
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draft_model="draft-tiny",
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strategy="eagle",
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)
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output = engine.generate(
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"Write a blog post about AI speculation:",
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max_tokens=1024,
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temperature=0.7,
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)
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```
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---
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## Architecture
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```mermaid
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flowchart TB
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subgraph Input["Input Processing"]
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A[Prompt Tokens] --> B[Token Embedding]
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end
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subgraph Draft["Draft Stage"]
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B --> C{Eagle / Medusa?}
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C -->|Eagle| D[Autoregressive Draft Model]
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C -->|Medusa| E[Multi-Head Predictor]
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D --> F[Draft Token Tree]
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E --> F
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end
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subgraph Verify["Verification Stage"]
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F --> G[Target Model Forward Pass]
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G --> H[Rejection Sampling]
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H --> I{Accepted?}
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I -->|Yes| J[Append All Tokens]
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I -->|No| K[Append up to Accepted Position]
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end
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subgraph Output["Output"]
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J --> L[Decoded Text]
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K --> L
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L --> M[Next Iteration]
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M --> A
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end
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```
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---
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## Benchmarks
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| Model | Baseline (tokens/s) | SpecInferKit (tokens/s) | Speedup | Memory (GB) |
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|---|---|---|---|---|
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| **LLaMA-3.1-8B** | 48.2 | 124.6 | **2.6×** | 16 → 9 |
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| **LLaMA-3.1-70B** | 12.1 | 31.8 | **2.6×** | 140 → 72 |
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| **LLaMA-3.1-405B** | 2.8 | 7.3 | **2.6×** | 810 → 420 |
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| **Mistral-7B** | 55.3 | 138.2 | **2.5×** | 14 → 8 |
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| **DeepSeek-V3** | 8.9 | 23.5 | **2.6×** | 190 → 98 |
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> Benchmarks measured on NVIDIA H100 (80GB) with batch size 1, input length 512, output length 256.
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---
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## Modules
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```
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specinferkit/
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├── algorithms/ # Speculation strategies (eagle, medusa)
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├── trainer/ # Draft model training (online, distributed)
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├── quantization/ # FP8 compression utilities
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├── serving/ # Inference server & client
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├── data/ # Dataset loaders and tokenizers
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├── eval/ # Accuracy and latency benchmarks
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├── cli/ # Command-line interface
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└── utils/ # Shared helpers and logging
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├── algorithms/ # Speculation strategies
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│ ├── eagle.py # Eagle draft model
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│ └── medusa.py # Medusa multi-head
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├── trainer/ # Draft model training
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│ ├── base.py # Base trainer
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│ ├── online.py # Online fine-tuning
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│ └── distributed.py # Multi-GPU training
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├── quantization/ # FP8 compression
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│ └── fp8.py # FP8 quantizer
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├── serving/ # Inference server
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│ ├── server.py # gRPC serving
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│ └── client.py # Python client
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├── data/ # Dataset loaders
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├── eval/ # Benchmarks
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├── cli/ # Command-line interface
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└── utils/ # Shared helpers
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```
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## Benchmarks
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---
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## Contributing
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| Model | Baseline (tokens/s) | SpecInferKit (tokens/s) | Speedup |
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|---|---|---|---|
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| LLaMA-3.1-8B | 48.2 | 124.6 | 2.6x |
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| LLaMA-3.1-70B | 12.1 | 31.8 | 2.6x |
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| LLaMA-3.1-405B | 2.8 | 7.3 | 2.6x |
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We welcome contributions! See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.
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## References
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- **Report bugs** — [Open an issue](https://github.com/Crynge/SpecInferKit/issues)
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- **Suggest features** — Start a [discussion](https://github.com/Crynge/SpecInferKit/discussions)
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- **Submit PRs** — Fork and open a pull request
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- Eagle: [Speculative Decoding with Accelerated Drafting](https://arxiv.org/abs/2402.01680)
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- Medusa: [Simple Framework for Speculative Decoding](https://arxiv.org/abs/2401.10774)
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---
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## License
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[MIT](LICENSE)
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---
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## 🌐 Crynge Ecosystem
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All repos are **free and open-source**. ⭐ Star what you use!
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| Category | Repos |
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|---|---|
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| **LLM & AI** | [SpecInferKit](https://github.com/Crynge/SpecInferKit) · [AetherAgents](https://github.com/Crynge/AetherAgents) · [PromptShield](https://github.com/Crynge/PromptShield) |
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| **Marketing** | [AdVerify](https://github.com/Crynge/AdVerify) · [Attributor](https://github.com/Crynge/Attributor) · [InfluencerHub](https://github.com/Crynge/InfluencerHub) · [EdgePersona](https://github.com/Crynge/EdgePersona) · [AdVantage](https://github.com/Crynge/AdVantage) · [BrandMuse](https://github.com/Crynge/BrandMuse) · [CampaignForge](https://github.com/Crynge/CampaignForge) |
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| **Simulation** | [CivSim](https://github.com/Crynge/CivSim) · [EvalScope](https://github.com/Crynge/EvalScope) |
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| **Operations** | [OpsFlow](https://github.com/Crynge/OpsFlow) |
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<div align="center">
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<sub>Built by <a href="https://github.com/Crynge">Crynge</a> · ⭐ Star us on GitHub!</sub>
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</div>

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