Instructions to use ToPo-ToPo/DeepSeek-V4-Flash-0731-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ToPo-ToPo/DeepSeek-V4-Flash-0731-mlx-4bit 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("ToPo-ToPo/DeepSeek-V4-Flash-0731-mlx-4bit")

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

MLX LM

How to use ToPo-ToPo/DeepSeek-V4-Flash-0731-mlx-4bit with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "ToPo-ToPo/DeepSeek-V4-Flash-0731-mlx-4bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "ToPo-ToPo/DeepSeek-V4-Flash-0731-mlx-4bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "ToPo-ToPo/DeepSeek-V4-Flash-0731-mlx-4bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Atomic Chat

DeepSeek-V4-Flash-0731-mlx-4bit

File size: 47 Bytes

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{
  "processor_class": "DeepseekV4Processor"
}