Instructions to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Use Docker

docker model run hf.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "abenzerps/ZDTaichu5.0-9B-DSpark-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "abenzerps/ZDTaichu5.0-9B-DSpark-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Ollama
How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with Ollama:
```
ollama run hf.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
```
Unsloth Desktop

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with Docker Model Runner:
```
docker model run hf.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
```

Lemonade

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.ZDTaichu5.0-9B-DSpark-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

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 abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

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 "abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

ZDTaichu5.0-9B DSpark GGUF

GGUF files for ZDTaichu5.0-9B-DSpark, the official semi-autoregressive speculative decoding draft model developed by the Zi Dong Tai Chu team to accelerate ZDTaichu5.0-9B.

This is a speculative decoding draft model (D-Spark / DFlash), not a standalone general model. It must be paired with the primary ZDTaichu5.0-9B GGUF model during inference to increase generation speeds by up to 60–85%.

Benchmarks

Benchmark results reported by TaichuAI for the original ZDTaichu5.0-9B foundation model. These figures are not measurements of this GGUF conversion.

GGUF files

Quantization	DSpark Draft File	Draft Size	Paired Base Model File
BF16	ZDTaichu5.0-9B-DSpark-BF16.gguf	4.40 GB	TaichuAI/ZDTaichu5.0-9B (Original Weights)
Q8_0	ZDTaichu5.0-9B-DSpark-Q8_0.gguf	2.34 GB	ZDTaichu5.0-9B-Q8_0.gguf (9.53 GB)
Q6_K	ZDTaichu5.0-9B-DSpark-Q6_K.gguf	1.81 GB	ZDTaichu5.0-9B-Q6_K.gguf (7.36 GB)
Q5_K_M	ZDTaichu5.0-9B-DSpark-Q5_K_M.gguf	1.67 GB	ZDTaichu5.0-9B-Q5_K_M.gguf (6.47 GB)
Q4_K_M	ZDTaichu5.0-9B-DSpark-Q4_K_M.gguf	1.53 GB	ZDTaichu5.0-9B-Q4_K_M.gguf (5.63 GB)
Q4_0	ZDTaichu5.0-9B-DSpark-Q4_0.gguf	1.51 GB	ZDTaichu5.0-9B-Q4_0.gguf (5.31 GB)

Draft model architecture

Framework: DSpark (semi-autoregressive DFlash backbone + chained Markov head).
Target Layers: Extracts auxiliary hidden states from target layers [1, 8, 15, 22, 29].
Block Size: 8 tokens drafted per forward pass (dflash.block_size = 8).
Target Model: ZDTaichu5.0-9B GGUF.

Usage

Use this draft model alongside the primary target model abenzerps/ZDTaichu5.0-9B-GGUF with llama.cpp (llama-cli or llama-server):

Text generation with Speculative Decoding (`llama-cli`)

llama-cli \
  -m ZDTaichu5.0-9B-Q4_K_M.gguf \
  -md ZDTaichu5.0-9B-DSpark-Q4_K_M.gguf \
  --spec-type draft-dspark \
  --spec-draft-n-max 8 \
  -c 8192 --jinja \
  --temp 0.7 --top-p 0.95 \
  -p "Explain why reproducible builds matter."

Multimodal vision understanding with Speculative Decoding (`llama-cli`)

llama-cli \
  -m ZDTaichu5.0-9B-Q4_K_M.gguf \
  -md ZDTaichu5.0-9B-DSpark-Q4_K_M.gguf \
  --mmproj mmproj-ZDTaichu5.0-9B-BF16.gguf \
  --spec-type draft-dspark \
  --spec-draft-n-max 8 \
  --image path/to/image.jpg \
  -p "Describe what is shown in this image in detail."

OpenAI-compatible server with Speculative Decoding (`llama-server`)

llama-server \
  -m ZDTaichu5.0-9B-Q4_K_M.gguf \
  -md ZDTaichu5.0-9B-DSpark-Q4_K_M.gguf \
  --mmproj mmproj-ZDTaichu5.0-9B-BF16.gguf \
  --spec-type draft-dspark \
  --spec-draft-n-max 8 \
  -c 8192 --jinja -fa on --host 0.0.0.0 --port 8080

Increase context -c up to 131,072 tokens (128K) when sufficient memory is available.

Source and build

Source draft model: TaichuAI/ZDTaichu5.0-9B-DSpark
Target base model: TaichuAI/ZDTaichu5.0-9B
Conversion: ggml-org/llama.cpp commit 7ceed8737fdb4eb09b4760e77bd12d38012de5a8
License: Apache-2.0
Checksums: SHA256SUMS.txt

Downloads last month: 974

GGUF

Model size

2B params

Architecture

dflash

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

16-bit

Model tree for abenzerps/ZDTaichu5.0-9B-DSpark-GGUF

Base model

TaichuAI/ZDTaichu5.0-9B

Quantized

(6)

this model

Collection including abenzerps/ZDTaichu5.0-9B-DSpark-GGUF

ZDTaichu5.0-9B

Collection

ZDTaichu5.0-9B model family releases, including GGUF and MLX conversions. • 5 items • Updated 8 days ago

ZDTaichu5.0-9B DSpark GGUF

Benchmarks

GGUF files

Draft model architecture

Usage

Text generation with Speculative Decoding (llama-cli)

Multimodal vision understanding with Speculative Decoding (llama-cli)

OpenAI-compatible server with Speculative Decoding (llama-server)

Source and build

Model tree for abenzerps/ZDTaichu5.0-9B-DSpark-GGUF

Collection including abenzerps/ZDTaichu5.0-9B-DSpark-GGUF

Text generation with Speculative Decoding (`llama-cli`)

Multimodal vision understanding with Speculative Decoding (`llama-cli`)

OpenAI-compatible server with Speculative Decoding (`llama-server`)