Instructions to use NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4 with Transformers:

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

pipe = pipeline("image-text-to-text", model="NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4")
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("NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4")
model = AutoModelForMultimodalLM.from_pretrained("NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4", device_map="auto")
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?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4",
		"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/NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4

SGLang

How to use NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4 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 "NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4" \
    --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": "NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4",
		"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 "NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4" \
        --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": "NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4",
		"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"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4 with Docker Model Runner:
```
docker model run hf.co/NeuralNet-Hub/Qwen3.6-35B-A3B-NVFP4
```

hdnh2006 commited on May 14

Commit

681d291

verified ·

1 Parent(s): c2446e0

Upload folder using huggingface_hub

Browse files

Files changed (5) hide show

config.json +1 -1
generation_config.json +1 -1
model.safetensors +2 -2
model.safetensors.index.json +2 -2
processor_config.json +4 -1

config.json CHANGED Viewed

@@ -488,7 +488,7 @@
     "vocab_size": 248320
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   "tie_word_embeddings": false,
-  "transformers_version": "5.5.0",
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   "vision_config": {
     "deepstack_visual_indexes": [],

     "vocab_size": 248320
   },
   "tie_word_embeddings": false,
+  "transformers_version": "5.3.0",
   "video_token_id": 248057,
   "vision_config": {
     "deepstack_visual_indexes": [],

generation_config.json CHANGED Viewed

@@ -9,5 +9,5 @@
   "temperature": 1.0,
   "top_k": 20,
   "top_p": 0.95,
-  "transformers_version": "5.5.0"
 }

   "temperature": 1.0,
   "top_k": 20,
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 }

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processor_config.json CHANGED Viewed

@@ -1,5 +1,6 @@
 {
   "image_processor": {
     "do_convert_rgb": true,
     "do_normalize": true,
     "do_rescale": true,
@@ -9,7 +10,7 @@
       0.5,
       0.5
     ],
-    "image_processor_type": "Qwen2VLImageProcessor",
     "image_std": [
       0.5,
       0.5,
@@ -27,6 +28,8 @@
   },
   "processor_class": "Qwen3VLProcessor",
   "video_processor": {
     "do_convert_rgb": true,
     "do_normalize": true,
     "do_rescale": true,

 {
   "image_processor": {
+    "data_format": "channels_first",
     "do_convert_rgb": true,
     "do_normalize": true,
     "do_rescale": true,
       0.5,
       0.5
     ],
+    "image_processor_type": "Qwen2VLImageProcessorFast",
     "image_std": [
       0.5,
       0.5,
   },
   "processor_class": "Qwen3VLProcessor",
   "video_processor": {
+    "data_format": "channels_first",
+    "default_to_square": true,
     "do_convert_rgb": true,
     "do_normalize": true,
     "do_rescale": true,