Instructions to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF")
model = AutoModelForMultimodalLM.from_pretrained("nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF", device_map="auto")

llama-cpp-python

How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF",
	filename="Qwen3.5-9B-Holodeck-Lounge-IQ4_NL.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": [
				{
					"type": "text",
					"text": "Describe this image in one sentence."
				},
				{
					"type": "image_url",
					"image_url": {
						"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
					}
				}
			]
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-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 nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf nightmedia/Qwen3.5-9B-Holodeck-Lounge-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 nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf nightmedia/Qwen3.5-9B-Holodeck-Lounge-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 nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf nightmedia/Qwen3.5-9B-Holodeck-Lounge-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 nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M

Use Docker

docker model run hf.co/nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nightmedia/Qwen3.5-9B-Holodeck-Lounge-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": "nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M

SGLang

How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Ollama
How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF with Ollama:
```
ollama run hf.co/nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M
```

Unsloth Studio

How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF 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 nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF 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 nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF to start chatting

How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M

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": "nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-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 nightmedia/Qwen3.5-9B-Holodeck-Lounge-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 nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf nightmedia/Qwen3.5-9B-Holodeck-Lounge-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 "nightmedia/Qwen3.5-9B-Holodeck-Lounge-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"

Docker Model Runner
How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF with Docker Model Runner:
```
docker model run hf.co/nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M
```

Lemonade

How to use nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull nightmedia/Qwen3.5-9B-Holodeck-Lounge-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwen3.5-9B-Holodeck-Lounge-GGUF-Q4_K_M

List all available models

lemonade list

nightmedia commited on 2 days ago

Commit

c86db41

verified ·

1 Parent(s): 67f9e32

Add files using upload-large-folder tool

Browse files

Files changed (10) hide show

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Qwen3.5-9B-Holodeck-Lounge-IQ4_NL.gguf +3 -0
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README.md +27 -0
config.json +112 -0
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mtp-f16.gguf +3 -0
tokenizer.json +3 -0

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README.md ADDED Viewed

	@@ -0,0 +1,27 @@

+---
+{}
+---
+# Qwen3.5-9B-Holodeck-Lounge-GGUF
+## Use with mlx
+```bash
+pip install mlx-lm
+```
+```python
+from mlx_lm import load, generate
+model, tokenizer = load("Qwen3.5-9B-Holodeck-Lounge-GGUF")
+prompt = "hello"
+if tokenizer.chat_template is not None:
+    messages = [{"role": "user", "content": prompt}]
+    prompt = tokenizer.apply_chat_template(
+        messages, add_generation_prompt=True, return_dict=False,
+    )
+response = generate(model, tokenizer, prompt=prompt, verbose=True)
+```

config.json ADDED Viewed

	@@ -0,0 +1,112 @@

+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "dtype": "bfloat16",
+  "image_token_id": 248056,
+  "model_name": "/mnt/d/Qwen3.5-9B-heretic-v2",
+  "model_type": "qwen3_5",
+  "pad_token_id": 248044,
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_output_gate": true,
+    "bos_token_id": null,
+    "dtype": "bfloat16",
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+    "hidden_act": "silu",
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+    "layer_types": [
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+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
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+      "linear_attention",
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+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
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+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention"
+    ],
+    "linear_conv_kernel_dim": 4,
+    "linear_key_head_dim": 128,
+    "linear_num_key_heads": 16,
+    "linear_num_value_heads": 32,
+    "linear_value_head_dim": 128,
+    "mamba_ssm_dtype": "float32",
+    "max_position_embeddings": 262144,
+    "mlp_only_layers": [],
+    "model_type": "qwen3_5_text",
+    "mtp_num_hidden_layers": 1,
+    "mtp_use_dedicated_embeddings": false,
+    "num_attention_heads": 16,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 4,
+    "pad_token_id": null,
+    "partial_rotary_factor": 0.25,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
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+      "mrope_section": [
+        11,
+        11,
+        10
+      ],
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+      "rope_theta": 10000000,
+      "rope_type": "default"
+    },
+    "tie_word_embeddings": false,
+    "use_cache": true,
+    "vocab_size": 248320
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.12.1",
+  "unsloth_version": "2026.5.8",
+  "video_token_id": 248057,
+  "vision_config": {
+    "deepstack_visual_indexes": [],
+    "depth": 27,
+    "dtype": "bfloat16",
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_size": 1152,
+    "in_channels": 3,
+    "initializer_range": 0.02,
+    "intermediate_size": 4304,
+    "model_type": "qwen3_5",
+    "num_heads": 16,
+    "num_position_embeddings": 2304,
+    "out_hidden_size": 4096,
+    "patch_size": 16,
+    "spatial_merge_size": 2,
+    "temporal_patch_size": 2
+  },
+  "vision_end_token_id": 248054,
+  "vision_start_token_id": 248053
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