Instructions to use inferencerlabs/Ling-2.6-flash-MLX-9bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inferencerlabs/Ling-2.6-flash-MLX-9bit 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("inferencerlabs/Ling-2.6-flash-MLX-9bit")

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
LM Studio

Pi new

How to use inferencerlabs/Ling-2.6-flash-MLX-9bit with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "inferencerlabs/Ling-2.6-flash-MLX-9bit"

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": "inferencerlabs/Ling-2.6-flash-MLX-9bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use inferencerlabs/Ling-2.6-flash-MLX-9bit 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 "inferencerlabs/Ling-2.6-flash-MLX-9bit"

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 inferencerlabs/Ling-2.6-flash-MLX-9bit

Run Hermes

hermes

MLX LM

How to use inferencerlabs/Ling-2.6-flash-MLX-9bit with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "inferencerlabs/Ling-2.6-flash-MLX-9bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "inferencerlabs/Ling-2.6-flash-MLX-9bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "inferencerlabs/Ling-2.6-flash-MLX-9bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

inferencerlabs commited on 9 days ago

Commit

45bc60e

verified ·

1 Parent(s): bba32f8

Upload model file

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README.md +0 -5

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@@ -9,11 +9,6 @@ base_model_relation: quantized
 library_name: mlx
 pipeline_tag: text-generation
 ---
-# NOTICE
-<marquee direction="left" width="400">
-    <h1 style="font-size: 60px; color: red;">CURRENTLY UPLOADING...&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</h1>
-</marquee>
 **See Ling-2.6-flash in action - [demonstration videos](https://youtube.com/xcreate)**
 #### Tested with an M3 Ultra 512 GiB using [Inferencer app v1.11.2](https://inferencer.com)

 library_name: mlx
 pipeline_tag: text-generation
 ---
 **See Ling-2.6-flash in action - [demonstration videos](https://youtube.com/xcreate)**
 #### Tested with an M3 Ultra 512 GiB using [Inferencer app v1.11.2](https://inferencer.com)