Instructions to use imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64 with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64 with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64 with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64 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 "imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64"

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 imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64 with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64"

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "imaadd05/Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64 / tokenizer_config.json

imaadd05

Stage checksum-validated 6-bit candidate pending native Mac release gates

9104747 verified about 19 hours ago

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	{
	"added_tokens_decoder": {
	"0": {
	"content": "<\|endoftext\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
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	"special": true
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	"21": {
	"content": "<system>",
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	"22": {
	"content": "</system>",
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	"23": {
	"content": "<think>",
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	"24": {
	"content": "</think>",
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	"rstrip": false,
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	},
	"25": {
	"content": "<user>",
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	"26": {
	"content": "</user>",
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	"27": {
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	"28": {
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	"29": {
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	"30": {
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	"33": {
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	"34": {
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	"additional_special_tokens": [
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	"<reponame>",
	"<system>",
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	"<user>",
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	"<\|im_start\|>",
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	],
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	"eos_token": "<\|im_end\|>",
	"extra_special_tokens": {},
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	"pad_token": "<\|endoftext\|>",
	"tokenizer_class": "PreTrainedTokenizerFast",
	"unk_token": "<\|endoftext\|>"
	}