Instructions to use deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16 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("deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16")

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 deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16 with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16"

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": "deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16 with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16 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 "deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16"

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 deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16 with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16"

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 "deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16" \
  --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"

Ornith-1.0-35B-MLX-oQ8-FP16 / README.md

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	---
	language: en
	license: mit
	pipeline_tag: text-generation
	tags:
	- mlx
	library_name: mlx
	base_model: deepreinforce-ai/Ornith-1.0-35B
	---

	This model was converted to MLX format and quantized from [Ornith-1.0-35B](https://huggingface.co/deepreinforce-ai/Ornith-1.0-35B) using [oMLX](https://github.com/jundot/omlx).

	>[!CAUTION]
	>The conversion required to stack expert MLP weights into fused per-layer tensors. Treat this as an experiment and act accordingly.

	## What is "oQ"?

	See ["oQ: oMLX Universal Dynamic Quantization"](https://github.com/jundot/omlx/blob/main/docs/oQ_Quantization.md) for details.

	## Quantizations

	\| Text-Only \| Vision-Language \| Text-Only FP16 \| Vision-Language FP16 \|
	\|---------------\|------------------\|--------------------\|-----------------------\|
	\| [MLX-oQ8][01] \| [MLX-VL-oQ8][05] \| [MLX-oQ8-FP16][09] \| [MLX-VL-oQ8-FP16][13] \|
	\| [MLX-oQ6][02] \| [MLX-VL-oQ6][06] \| [MLX-oQ6-FP16][10] \| [MLX-VL-oQ6-FP16][14] \|
	\| [MLX-oQ5][03] \| [MLX-VL-oQ5][07] \| [MLX-oQ5-FP16][11] \| [MLX-VL-oQ5-FP16][15] \|
	\| [MLX-oQ4][04] \| [MLX-VL-oQ4][08] \| [MLX-oQ4-FP16][12] \| [MLX-VL-oQ4-FP16][16] \|

	## What is "VL"?

	"VL" is Vision-Language, meaning quantization preserves the original model's multimodality.

	No "VL" means quantization is Text-Only.

	## What is "FP16"?

	"FP16" is an M1/M2 Apple Silicon tweak that delivers a very noticeable prompt processing boost, because older M-series lack native BF16 hardware support. See ["Metal FP32 Vs BF16 Vs FP16 benchmark"](https://github.com/deepsweet/metal-fp32-bf16-fp16) for details.

	No "FP16" means quantization is better suited for M3+ Apple Silicon.

	[01]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-oQ8
	[02]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-oQ6
	[03]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-oQ5
	[04]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-oQ4
	[05]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-VL-oQ8
	[06]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-VL-oQ6
	[07]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-VL-oQ5
	[08]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-VL-oQ4
	[09]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-oQ8-FP16
	[10]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-oQ6-FP16
	[11]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-oQ5-FP16
	[12]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-oQ4-FP16
	[13]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-VL-oQ8-FP16
	[14]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-VL-oQ6-FP16
	[15]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-VL-oQ5-FP16
	[16]: https://huggingface.co/deepsweet/Ornith-1.0-35B-MLX-VL-oQ4-FP16