Instructions to use inferencerlabs/Solar-Open-100B-MLX-6.5bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inferencerlabs/Solar-Open-100B-MLX-6.5bit 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/Solar-Open-100B-MLX-6.5bit")

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/Solar-Open-100B-MLX-6.5bit 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/Solar-Open-100B-MLX-6.5bit"

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/Solar-Open-100B-MLX-6.5bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use inferencerlabs/Solar-Open-100B-MLX-6.5bit 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/Solar-Open-100B-MLX-6.5bit"

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/Solar-Open-100B-MLX-6.5bit

Run Hermes

hermes

MLX LM

How to use inferencerlabs/Solar-Open-100B-MLX-6.5bit 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/Solar-Open-100B-MLX-6.5bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "inferencerlabs/Solar-Open-100B-MLX-6.5bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "inferencerlabs/Solar-Open-100B-MLX-6.5bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

NOTICE

No longer available on HF due to storage restrictions - archived here

Information

See Solar-Open-100B MLX in action - demonstration video

q6.5bit mixed quant typically achieves 1.128 perplexity in our testing

Quantization	Perplexity
q2.5	41.293
q3.5	1.900
q4.5	1.168
q4.8	1.140
q5.5	1.141
q6.5	1.128
q8.5	1.128

Usage Notes

Tested on a M3 Ultra using Inferencer app v1.9.1

Single inference ~45 tokens/s @ 1000 tokens
Batched inference ~72 total tokens/s across four inferences
Memory usage: ~78 GB

Quantized with a modified version of MLX 0.30

For more details see demonstration video or visit Solar-Open-100B.

Downloads last month: 87

Safetensors

Model size

103B params

Tensor type

BF16

U32

F32

Model tree for inferencerlabs/Solar-Open-100B-MLX-6.5bit

Base model

upstage/Solar-Open-100B

Quantized

(14)

this model