Instructions to use Solstice-AI/DeepSeek-V4-Flash-MTP-DSpark-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Solstice-AI/DeepSeek-V4-Flash-MTP-DSpark-MLX with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("Solstice-AI/DeepSeek-V4-Flash-MTP-DSpark-MLX") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use Solstice-AI/DeepSeek-V4-Flash-MTP-DSpark-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "Solstice-AI/DeepSeek-V4-Flash-MTP-DSpark-MLX" --prompt "Once upon a time"
- Atomic Chat
DeepSeek-V4-Flash-MTP-DSpark-MLX
Official Solstice-AI Speculative Decoding Drafter for Apple Silicon • Native Multi-Token Prediction (MTP) • 2x–3x Throughput Boost for DeepSeek-V4-Flash-Vision-Exp
Designed to pair seamlessly with Solstice-AI/DeepSeek-V4-Flash-Vision-Exp-MLX
Overview
Solstice-AI/DeepSeek-V4-Flash-MTP-DSpark-MLX is the standalone Multi-Token Prediction (MTP) speculative drafter model optimized for Apple Silicon via Apple's MLX framework.
When paired with the target foundation model Solstice-AI/DeepSeek-V4-Flash-Vision-Exp-MLX, this drafter model speculatively generates multiple candidate tokens per decoding step with zero loss in mathematical or algorithmic accuracy, increasing generation speeds by 2.2x to 3.1x across common coding, reasoning, and document analysis workloads.
Usage with MLX-LM
from mlx_lm import load, generate
target_model_id = "Solstice-AI/DeepSeek-V4-Flash-Vision-Exp-MLX"
draft_model_id = "Solstice-AI/DeepSeek-V4-Flash-MTP-DSpark-MLX"
model, tokenizer = load(target_model_id, draft_model=draft_model_id)
prompt = "Explain quantum error correction using the surface code."
response = generate(model, tokenizer, prompt=prompt, max_tokens=1024, verbose=True)
print(response)
License & Attribution
- Architecture: DeepSeek-AI (DeepSeek License)
- Packaging & Optimization: Solstice-AI
- Downloads last month
- 118
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Model tree for Solstice-AI/DeepSeek-V4-Flash-MTP-DSpark-MLX
Base model
deepseek-ai/DeepSeek-V4-Flash-Vision-Exp