Instructions to use inferencerlabs/DeepSeek-V4-Flash-MLX-9bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use inferencerlabs/DeepSeek-V4-Flash-MLX-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("inferencerlabs/DeepSeek-V4-Flash-MLX-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 inferencerlabs/DeepSeek-V4-Flash-MLX-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 "inferencerlabs/DeepSeek-V4-Flash-MLX-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": "inferencerlabs/DeepSeek-V4-Flash-MLX-9bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use inferencerlabs/DeepSeek-V4-Flash-MLX-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 "inferencerlabs/DeepSeek-V4-Flash-MLX-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 inferencerlabs/DeepSeek-V4-Flash-MLX-9bit
Run Hermes
hermes
- MLX LM
How to use inferencerlabs/DeepSeek-V4-Flash-MLX-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 "inferencerlabs/DeepSeek-V4-Flash-MLX-9bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "inferencerlabs/DeepSeek-V4-Flash-MLX-9bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "inferencerlabs/DeepSeek-V4-Flash-MLX-9bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
Update README.md
Browse files
README.md
CHANGED
|
@@ -20,7 +20,7 @@ pipeline_tag: text-generation
|
|
| 20 |
In this build, the 4-bit pre-quantized weights of the base model were repacked (rather than dequantized and re-quantized to 9-bit), as this approach performed slightly better in our initial coding tests. All remaining weights were quantized to 9-bit. It also includes a temporary chat template. Stay tuned for updates.
|
| 21 |
</p>
|
| 22 |
|
| 23 |
-

|
| 26 |
##### For more details see our [demonstration videos](https://youtube.com/xcreate) or visit [DeepSeek-V4-Flash](https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash).
|
|
|
|
| 20 |
In this build, the 4-bit pre-quantized weights of the base model were repacked (rather than dequantized and re-quantized to 9-bit), as this approach performed slightly better in our initial coding tests. All remaining weights were quantized to 9-bit. It also includes a temporary chat template. Stay tuned for updates.
|
| 21 |
</p>
|
| 22 |
|
| 23 |
+

|
| 24 |
|
| 25 |
##### Quantized with a modified version of [MLX](https://github.com/ml-explore/mlx)
|
| 26 |
##### For more details see our [demonstration videos](https://youtube.com/xcreate) or visit [DeepSeek-V4-Flash](https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash).
|