Instructions to use ulises-c/Qwen3.5-9B-MTP-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ulises-c/Qwen3.5-9B-MTP-8bit 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("ulises-c/Qwen3.5-9B-MTP-8bit") 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
- Pi
How to use ulises-c/Qwen3.5-9B-MTP-8bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "ulises-c/Qwen3.5-9B-MTP-8bit"
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": "ulises-c/Qwen3.5-9B-MTP-8bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use ulises-c/Qwen3.5-9B-MTP-8bit 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 "ulises-c/Qwen3.5-9B-MTP-8bit"
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 ulises-c/Qwen3.5-9B-MTP-8bit
Run Hermes
hermes
- OpenClaw new
How to use ulises-c/Qwen3.5-9B-MTP-8bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "ulises-c/Qwen3.5-9B-MTP-8bit"
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 "ulises-c/Qwen3.5-9B-MTP-8bit" \ --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"
- MLX LM
How to use ulises-c/Qwen3.5-9B-MTP-8bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "ulises-c/Qwen3.5-9B-MTP-8bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "ulises-c/Qwen3.5-9B-MTP-8bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ulises-c/Qwen3.5-9B-MTP-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
Qwen3.5-9B-MTP-8bit
This repository contains 8-bit quantized Multi-Token Prediction (MTP) drafter weights for Qwen/Qwen3.5-9B, for use with mlx-vlm speculative decoding. It was quantized from mlx-community/Qwen3.5-9B-MTP-bf16.
This is not a standalone chat or text-generation model. Load it as the draft model alongside a compatible Qwen3.5 9B target checkpoint.
Compatible target models
Pair this drafter with a Qwen3.5-9B target checkpoint. Recommended MLX targets (match target precision to your memory budget):
mlx-community/Qwen3.5-9B-8bit— recommended pairing for this 8-bit draftermlx-community/Qwen3.5-9B-6bit
Use with mlx-vlm
uv run mlx_vlm.generate \
--model mlx-community/Qwen3.5-9B-8bit \
--draft-model ulises-c/Qwen3.5-9B-MTP-8bit \
--prompt "Hi, how are you?" \
--max-tokens 256 \
--enable-thinking
For local weights:
uv run mlx_vlm.generate \
--model /path/to/target-model \
--draft-model /path/to/Qwen3.5-9B-MTP-8bit \
--prompt "Hi, how are you?" \
--max-tokens 256 \
--enable-thinking
Model Details
- Model type:
qwen3_5_mtp - MTP block size:
2 - Target architecture: Qwen3.5 9B
- Precision: 8-bit (affine, group size 64) — 8.501 bits per weight
- Runtime: MLX /
mlx-vlm - Format: Safetensors with MLX-compatible config and tokenizer files
Conversion
Quantized with mlx-vlm (the qwen3_5_mtp architecture is provided by mlx-vlm, not mlx-lm):
uvx --from 'mlx-vlm @ git+https://github.com/Blaizzy/mlx-vlm' mlx_vlm.convert \
--hf-path mlx-community/Qwen3.5-9B-MTP-bf16 \
--mlx-path Qwen3.5-9B-MTP-8bit \
-q --q-bits 8 --q-group-size 64
Intended Use
Use this repo only as a speculative decoding drafter for compatible Qwen3.5 9B checkpoints. The target model verifies drafted tokens, while this MTP model proposes candidate tokens per decoding step.
Limitations
This checkpoint requires runtime support for Qwen/DeepSeek MTP draft models in mlx-vlm. Standard standalone generation through generic Transformers APIs is not expected to work with this repository by itself.
Please refer to the upstream Qwen/Qwen3.5-9B model card and license terms for model usage constraints.
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