LM Studio
LM Studio is a desktop application that allows you to discover, download, and run local LLMs using various model formats (GGUF, GGML, SafeTensors). It provides an OpenAI-compatible API server for running these models locally.
Chat modelβ
LM Studio provides an OpenAI-compatible chat API interface that can be used with Tabby.
~/.tabby/config.toml
[model.chat.http]
kind = "openai/chat"
model_name = "deepseek-r1-distill-qwen-7b" # Example model
api_endpoint = "http://localhost:1234/v1" # LM Studio server endpoint with /v1 path
api_key = "" # No API key required for local deployment
Completion modelβ
LM Studio can be used for code completion tasks through its OpenAI-compatible completion API.
~/.tabby/config.toml
[model.completion.http]
kind = "openai/completion"
model_name = "starcoder2-7b" # Example code completion model
api_endpoint = "http://localhost:1234/v1"
api_key = ""
prompt_template = "<PRE> {prefix} <SUF>{suffix} <MID>" # Example prompt template for CodeLlama models
Embeddings modelβ
LM Studio supports embedding functionality through its OpenAI-compatible API.
~/.tabby/config.toml
[model.embedding.http]
kind = "openai/embedding"
model_name = "text-embedding-nomic-embed-text-v1.5"
api_endpoint = "http://localhost:1234/v1"
api_key = ""
Usage Notesβ
- Download and install LM Studio from their official website.
- Download your preferred model through LM Studio's model discovery interface.
- Start the local server by clicking the "Start Server" button in LM Studio.
- Configure Tabby to use LM Studio's API endpoint as shown in the examples above.
- The default server port is 1234, but you can change it in LM Studio's settings if needed.
- Make sure to append
/v1
to the API endpoint as LM Studio follows OpenAI's API structure.
LM Studio is particularly useful for running models locally without requiring complex setup or command-line knowledge. It supports a wide range of models and provides a user-friendly interface for model management and server operations.