# josstorer/rwkv-runner

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6,219 stars · 592 forks · TypeScript · mit

## Links

- GitHub: https://github.com/josStorer/RWKV-Runner
- Homepage: https://www.rwkv.com
- awesome-repositories: https://awesome-repositories.com/repository/josstorer-rwkv-runner.md

## Topics

`api` `api-client` `chatgpt` `llm` `rwkv` `tool` `wails`

## Tags

### Artificial Intelligence & ML

- [Local Model Runners](https://awesome-repositories.com/f/artificial-intelligence-ml/local-model-runners.md) — Launches RWKV large language models locally with one-click setup and automatic dependency management.
- [OpenAI-Compatible](https://awesome-repositories.com/f/artificial-intelligence-ml/artificial-intelligence-tooling/agent-and-tool-integrations/api-servers/openai-compatible.md) — Translates OpenAI chat and embedding request schemas into internal model calls for local inference.
- [Chat Interfaces](https://awesome-repositories.com/f/artificial-intelligence-ml/chat-interfaces.md) — Provides a built-in chat interface with presets, file attachments, and parameter tuning for RWKV models. ([source](https://cdn.jsdelivr.net/gh/josstorer/rwkv-runner@master/README.md))
- [State-Based Inference Engines](https://awesome-repositories.com/f/artificial-intelligence-ml/constant-time-inference-engines/state-based-inference-engines.md) — Runs the RWKV model as a recurrent neural network using a fixed-size state vector for linear-time inference.
- [Gated Linear Recurrent Layers](https://awesome-repositories.com/f/artificial-intelligence-ml/recurrent-neural-networks/gated-recurrent-units/gated-linear-recurrent-layers.md) — Runs the RWKV model as a recurrent neural network using a fixed-size state vector for linear-time inference.
- [LoRA Fine-Tuning Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/full-parameter-fine-tuning/custom-data-fine-tunings/lora-fine-tuning-tools.md) — Fine-tunes RWKV models on custom data using low-rank adaptation with a one-click training interface.
- [Multi-Backend GPU Inference Engines](https://awesome-repositories.com/f/artificial-intelligence-ml/inference-backends/multi-backend-gpu-inference-engines.md) — Switches between NVIDIA, AMD, Intel, and other GPU backends to run language model inference.
- [LoRA Fine-Tuning Pipelines](https://awesome-repositories.com/f/artificial-intelligence-ml/language-model-fine-tuning/partial-layer-fine-tunings/lora-fine-tuning-pipelines.md) — Implements a one-click LoRA fine-tuning pipeline for RWKV models on custom data.
- [LoRA Training](https://awesome-repositories.com/f/artificial-intelligence-ml/lora-training.md) — Adapts RWKV models to custom data using LoRA training with a single click on Windows. ([source](https://cdn.jsdelivr.net/gh/josstorer/rwkv-runner@master/README.md))
- [Model Downloaders](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-management/model-downloaders.md) — Downloads RWKV model weights and configuration files from remote sources for local use. ([source](https://cdn.jsdelivr.net/gh/josstorer/rwkv-runner@master/README.md))
- [Inference Compute Backends](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-optimization-and-inference/hardware-and-acceleration/hardware-abstraction-layers/inference-compute-backends.md) — Switches between CUDA, ROCm, and Vulkan backends to run RWKV models on various graphics hardware.
- [Model Format Converters](https://awesome-repositories.com/f/artificial-intelligence-ml/model-format-converters.md) — Provides a built-in command-line tool to convert models between RWKV, GGML, and PyTorch formats.
- [RWKV Format Converters](https://awesome-repositories.com/f/artificial-intelligence-ml/model-format-converters/rwkv-format-converters.md) — Converts model files between RWKV, GGML, and PyTorch formats using a built-in command-line tool. ([source](https://cdn.jsdelivr.net/gh/josstorer/rwkv-runner@master/README.md))
- [Text Embedding Generators](https://awesome-repositories.com/f/artificial-intelligence-ml/text-embedding-generators.md) — Generates vector embeddings from text inputs for semantic search and similarity tasks. ([source](https://cdn.jsdelivr.net/gh/josstorer/rwkv-runner@master/README.md))

### Part of an Awesome List

- [Local LLM Tools](https://awesome-repositories.com/f/awesome-lists/ai/local-llm-tools.md) — Runs large language models locally on consumer hardware with one-click setup and automatic dependency management.
- [Model Downloaders](https://awesome-repositories.com/f/awesome-lists/media/downloaders-and-managers/model-downloaders.md) — Downloads, inspects, and updates RWKV models through a built-in manager with automatic update support. ([source](https://cdn.jsdelivr.net/gh/josstorer/rwkv-runner@master/README.md))

### Development Tools & Productivity

- [Model Launchers](https://awesome-repositories.com/f/development-tools-productivity/launch-configuration-managers/model-launchers.md) — Launches large language models with a single click, automating dependency installation and configuration. ([source](https://cdn.jsdelivr.net/gh/josstorer/rwkv-runner@master/README.md))

### Web Development

- [OpenAI-Compatible Servers](https://awesome-repositories.com/f/web-development/openai-compatible-servers.md) — Ships a local server that exposes an OpenAI-compatible API for chat and embeddings. ([source](https://cdn.jsdelivr.net/gh/josstorer/rwkv-runner@master/README.md))
- [Preset-Based](https://awesome-repositories.com/f/web-development/web-based-ui-deployment/chat-interfaces/preset-based.md) — Provides a chat UI with configurable system prompts and parameter sets stored as reusable presets.

### Data & Databases

- [GPU Backend Switchers](https://awesome-repositories.com/f/data-databases/storage-scaling/gpu-acceleration-backends/gpu-backend-switchers.md) — Switches between GPU backends to run computations on NVIDIA, AMD, Intel, and other graphics cards. ([source](https://cdn.jsdelivr.net/gh/josstorer/rwkv-runner@master/README.md))
- [Unified GPU Backend Abstractions](https://awesome-repositories.com/f/data-databases/storage-scaling/gpu-acceleration-backends/unified-gpu-backend-abstractions.md) — Wraps CUDA, ROCm, and Vulkan behind a single inference interface with automatic backend switching.