Instructions to use satgeze/Qwen3.6-27B-DSpark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use satgeze/Qwen3.6-27B-DSpark with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="satgeze/Qwen3.6-27B-DSpark",
	filename="Qwen3.6-27B-DSpark.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use satgeze/Qwen3.6-27B-DSpark 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 satgeze/Qwen3.6-27B-DSpark
# Run inference directly in the terminal:
llama cli -hf satgeze/Qwen3.6-27B-DSpark

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf satgeze/Qwen3.6-27B-DSpark
# Run inference directly in the terminal:
llama cli -hf satgeze/Qwen3.6-27B-DSpark

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 satgeze/Qwen3.6-27B-DSpark
# Run inference directly in the terminal:
./llama-cli -hf satgeze/Qwen3.6-27B-DSpark

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 satgeze/Qwen3.6-27B-DSpark
# Run inference directly in the terminal:
./build/bin/llama-cli -hf satgeze/Qwen3.6-27B-DSpark

Use Docker

docker model run hf.co/satgeze/Qwen3.6-27B-DSpark

LM Studio
Jan
Ollama
How to use satgeze/Qwen3.6-27B-DSpark with Ollama:
```
ollama run hf.co/satgeze/Qwen3.6-27B-DSpark
```

Unsloth Studio

How to use satgeze/Qwen3.6-27B-DSpark with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for satgeze/Qwen3.6-27B-DSpark to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for satgeze/Qwen3.6-27B-DSpark to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for satgeze/Qwen3.6-27B-DSpark to start chatting

How to use satgeze/Qwen3.6-27B-DSpark with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf satgeze/Qwen3.6-27B-DSpark

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "satgeze/Qwen3.6-27B-DSpark"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use satgeze/Qwen3.6-27B-DSpark with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf satgeze/Qwen3.6-27B-DSpark

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 satgeze/Qwen3.6-27B-DSpark

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use satgeze/Qwen3.6-27B-DSpark with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf satgeze/Qwen3.6-27B-DSpark

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 "satgeze/Qwen3.6-27B-DSpark" \
  --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"

Docker Model Runner
How to use satgeze/Qwen3.6-27B-DSpark with Docker Model Runner:
```
docker model run hf.co/satgeze/Qwen3.6-27B-DSpark
```

Lemonade

How to use satgeze/Qwen3.6-27B-DSpark with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull satgeze/Qwen3.6-27B-DSpark

Run and chat with the model

lemonade run user.Qwen3.6-27B-DSpark-{{QUANT_TAG}}

List all available models

lemonade list

satgeze commited on 6 days ago

Commit

fe985ae

verified ·

1 Parent(s): ad82a4d

Upload config.json with huggingface_hub

Browse files

Files changed (1) hide show

config.json +74 -0

config.json ADDED Viewed

	@@ -0,0 +1,74 @@

+{
+  "architectures": [
+    "Qwen3DSparkModel"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_output_gate": true,
+  "block_size": 15,
+  "bos_token_id": 248044,
+  "confidence_head_with_markov": true,
+  "dtype": "bfloat16",
+  "enable_confidence_head": true,
+  "eos_token_id": 248044,
+  "full_attention_interval": 4,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 17408,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "linear_conv_kernel_dim": 4,
+  "linear_key_head_dim": 128,
+  "linear_num_key_heads": 16,
+  "linear_num_value_heads": 48,
+  "linear_value_head_dim": 128,
+  "mamba_ssm_dtype": "float32",
+  "markov_head_type": "vanilla",
+  "markov_rank": 256,
+  "mask_token_id": 248200,
+  "max_position_embeddings": 262144,
+  "max_window_layers": 28,
+  "model_type": "qwen3",
+  "mtp_num_hidden_layers": 1,
+  "mtp_use_dedicated_embeddings": false,
+  "num_anchors": 128,
+  "num_attention_heads": 32,
+  "num_hidden_layers": 5,
+  "num_key_value_heads": 8,
+  "num_target_layers": 64,
+  "output_gate_type": "swish",
+  "pad_token_id": null,
+  "partial_rotary_factor": 0.25,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "mrope_interleaved": true,
+    "mrope_section": [
+      11,
+      11,
+      10
+    ],
+    "partial_rotary_factor": 0.25,
+    "rope_theta": 10000000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "target_layer_ids": [
+    1,
+    16,
+    31,
+    46,
+    61
+  ],
+  "tie_word_embeddings": false,
+  "transformers_version": "5.10.2",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 248320
+}