feat: initial mlx 8bit quant, converted from LetheanNetwork/lemrd bf16 b718c8f
Snider Virgil commited on
How to use LetheanNetwork/lemrd-mlx-8bit with MLX:
# Make sure mlx-vlm is installed
# pip install --upgrade mlx-vlm
from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config
# Load the model
model, processor = load("LetheanNetwork/lemrd-mlx-8bit")
config = load_config("LetheanNetwork/lemrd-mlx-8bit")
# Prepare input
image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
prompt = "Describe this image."
# Apply chat template
formatted_prompt = apply_chat_template(
processor, config, prompt, num_images=1
)
# Generate output
output = generate(model, processor, formatted_prompt, image)
print(output)How to use LetheanNetwork/lemrd-mlx-8bit with Pi:
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "LetheanNetwork/lemrd-mlx-8bit"
# 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": "LetheanNetwork/lemrd-mlx-8bit"
}
]
}
}
}# Start Pi in your project directory: pi
How to use LetheanNetwork/lemrd-mlx-8bit with Hermes Agent:
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "LetheanNetwork/lemrd-mlx-8bit"
# 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 LetheanNetwork/lemrd-mlx-8bit
hermes