Instructions to use ToPo-ToPo/DeepSeek-V4-Flash-MTP-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ToPo-ToPo/DeepSeek-V4-Flash-MTP-bf16 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("ToPo-ToPo/DeepSeek-V4-Flash-MTP-bf16") 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 ToPo-ToPo/DeepSeek-V4-Flash-MTP-bf16 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "ToPo-ToPo/DeepSeek-V4-Flash-MTP-bf16" --prompt "Once upon a time"
ToPo-ToPo/DeepSeek-V4-Flash-MTP-bf16
MTP drafter for speculative decoding with DeepSeek-V4-Flash on Apple Silicon (mlx-vlm), in bf16 (3.4 GB).
This is a drafter, not a chat model — it is only useful as --draft-model.
Provenance (self-split from official weights)
- Source:
deepseek-ai/DeepSeek-V4-Flash(license: mit), whosemtp.*tensors live in a dedicated shard (model-00046-of-00046.safetensors) - Tool:
mlx-vlm 0.6.8—python -m mlx_vlm.speculative.drafters.deepseek_v4_mtp.split --model deepseek-ai/DeepSeek-V4-Flash --output . - Result: 45 tensors —
decoder.*(35),hc_head(3),e_proj/h_proj(2 each),enorm,hnorm,norm
Usage
Pair it with a DeepSeek-V4-Flash body and run the MTP round loop (--draft-kind mtp):
mlx_vlm.server --model ToPo-ToPo/DeepSeek-V4-Flash-0731-mlx-4bit \
--draft-model ToPo-ToPo/DeepSeek-V4-Flash-MTP-bf16 --draft-kind mtp
Speculative decoding is lossless, so the body's outputs are unchanged.
This drafter also works with the newer -0731 body even though it is split from the earlier release — the two
share hidden_size 4096. The MTP module bundled inside -0731 itself is a different architecture
(three modules built around main_proj) that mlx-vlm 0.6.8 does not implement.
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Model size
1B params
Tensor type
F32
·
BF16 ·
U8 ·
U32 ·
Hardware compatibility
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8-bit
Model tree for ToPo-ToPo/DeepSeek-V4-Flash-MTP-bf16
Base model
deepseek-ai/DeepSeek-V4-Flash