Instructions to use esc511/trip-optimizer-mutator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use esc511/trip-optimizer-mutator with MLX:

# Download the model from the Hub
pip install huggingface_hub[hf_xet]

huggingface-cli download --local-dir trip-optimizer-mutator esc511/trip-optimizer-mutator

llama-cpp-python

How to use esc511/trip-optimizer-mutator with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="esc511/trip-optimizer-mutator",
	filename="trip-mutator-q4km.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use esc511/trip-optimizer-mutator with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf esc511/trip-optimizer-mutator
# Run inference directly in the terminal:
llama-cli -hf esc511/trip-optimizer-mutator

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf esc511/trip-optimizer-mutator
# Run inference directly in the terminal:
llama-cli -hf esc511/trip-optimizer-mutator

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf esc511/trip-optimizer-mutator
# Run inference directly in the terminal:
./llama-cli -hf esc511/trip-optimizer-mutator

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf esc511/trip-optimizer-mutator
# Run inference directly in the terminal:
./build/bin/llama-cli -hf esc511/trip-optimizer-mutator

Use Docker

docker model run hf.co/esc511/trip-optimizer-mutator

LM Studio
Jan
Ollama
How to use esc511/trip-optimizer-mutator with Ollama:
```
ollama run hf.co/esc511/trip-optimizer-mutator
```

Unsloth Studio new

How to use esc511/trip-optimizer-mutator with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for esc511/trip-optimizer-mutator to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for esc511/trip-optimizer-mutator to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for esc511/trip-optimizer-mutator to start chatting

Pi new

How to use esc511/trip-optimizer-mutator with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "esc511/trip-optimizer-mutator"

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "esc511/trip-optimizer-mutator"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use esc511/trip-optimizer-mutator with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "esc511/trip-optimizer-mutator"

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default esc511/trip-optimizer-mutator

Run Hermes

hermes

Docker Model Runner
How to use esc511/trip-optimizer-mutator with Docker Model Runner:
```
docker model run hf.co/esc511/trip-optimizer-mutator
```

Lemonade

How to use esc511/trip-optimizer-mutator with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull esc511/trip-optimizer-mutator

Run and chat with the model

lemonade run user.trip-optimizer-mutator-{{QUANT_TAG}}

List all available models

lemonade list

trip-optimizer-mutator / README.md

esc511

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metadata

base_model: Qwen/Qwen3-4B-Instruct-2507
library_name: mlx
tags:
  - lora
  - mlx
  - trip-optimizer
  - travel
  - mutation
license: apache-2.0

trip-optimizer-mutator

MLX LoRA adapter for Qwen3-4B-Instruct-2507 that generates targeted, structured itinerary mutations for trip-optimizer.

Task

Given a trip profile, current plan, optimization goal, and constraints, the model outputs a scoped RFC 6902 JSON Patch proposal — one change at a time. trip-optimizer applies the patch deterministically and validates the result.

Input task field: mutate_plan

Supported mutation types: swap_activity, upgrade_meal, reorder_day, simplify_day, time_adjust, clarify

Usage with mlx-lm

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load(
    "Qwen/Qwen3-4B-Instruct-2507",
    adapter_path="esc511/trip-optimizer-mutator",
)

Usage with trip-optimizer

# After installing trip-optimizer
trip-optimizer setup   # pulls via Ollama

Training details

Base model: Qwen/Qwen3-4B-Instruct-2507
Method: MLX LoRA (r=8, alpha=20, dropout=0)
Layers: 32
Training iters: 600
Max sequence length: 8192
Hardware: Apple M5 Max 128 GB
Checkpoint: v2 (trip-mutator-4b-v0-mlx-r8-v2)

Input / Output schema

Full schemas at:

Input: trip_mutator_input.schema.json
Output: trip_mutator_output.schema.json