Instructions to use spicyneuron/GLM-5.1-MLX-2.9bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use spicyneuron/GLM-5.1-MLX-2.9bit 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("spicyneuron/GLM-5.1-MLX-2.9bit")

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 spicyneuron/GLM-5.1-MLX-2.9bit with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "spicyneuron/GLM-5.1-MLX-2.9bit"

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": "spicyneuron/GLM-5.1-MLX-2.9bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use spicyneuron/GLM-5.1-MLX-2.9bit 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 "spicyneuron/GLM-5.1-MLX-2.9bit"

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 spicyneuron/GLM-5.1-MLX-2.9bit

Run Hermes

hermes

MLX LM

How to use spicyneuron/GLM-5.1-MLX-2.9bit with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "spicyneuron/GLM-5.1-MLX-2.9bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "spicyneuron/GLM-5.1-MLX-2.9bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "spicyneuron/GLM-5.1-MLX-2.9bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

spicyneuron commited on Apr 10

Commit

7b96841

verified ·

1 Parent(s): 19d5dd6

Update README.md

Browse files

Files changed (1) hide show

README.md +12 -3

README.md CHANGED Viewed

@@ -32,9 +32,18 @@ MLX quantization options differ than llama.cpp, but the principles are the same:
 # Benchmarks
-(WIP)
-Tested with:
 ```
 mlx_lm.perplexity --sequence-length 2048 --seed 123

 # Benchmarks
+metric | baa-ai/GLM-5.1-RAM-270GB-MLX | 2.9bit (this model)
+--- | --- | ---
+bpw | 3.1096 | 2.9064
+peak memory (1024/512) | 291.257 | 272.358
+prompt tok/s (1024) | 194.958 ± 0.075 | 194.216 ± 0.167
+gen tok/s (512) | 21.381 ± 0.050 | 19.527 ± 0.035
+perplexity | 4.780 ± 0.020 | 4.118 ± 0.016
+hellaswag | 0.546 ± 0.011 | 0.59 ± 0.011
+piqa | 0.776 ± 0.01 | 0.794 ± 0.009
+winogrande | 0.668 ± 0.013 | 0.695 ± 0.013
+Tested on a Mac Studio M3 Ultra with:
 ```
 mlx_lm.perplexity --sequence-length 2048 --seed 123