Instructions to use llmfan46/Qwen3.5-35B-A3B-uncensored-heretic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use llmfan46/Qwen3.5-35B-A3B-uncensored-heretic with Transformers:

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

pipe = pipeline("image-text-to-text", model="llmfan46/Qwen3.5-35B-A3B-uncensored-heretic")
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("llmfan46/Qwen3.5-35B-A3B-uncensored-heretic")
model = AutoModelForMultimodalLM.from_pretrained("llmfan46/Qwen3.5-35B-A3B-uncensored-heretic")
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 llmfan46/Qwen3.5-35B-A3B-uncensored-heretic with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "llmfan46/Qwen3.5-35B-A3B-uncensored-heretic"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "llmfan46/Qwen3.5-35B-A3B-uncensored-heretic",
		"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/llmfan46/Qwen3.5-35B-A3B-uncensored-heretic

SGLang

How to use llmfan46/Qwen3.5-35B-A3B-uncensored-heretic 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 "llmfan46/Qwen3.5-35B-A3B-uncensored-heretic" \
    --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": "llmfan46/Qwen3.5-35B-A3B-uncensored-heretic",
		"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 "llmfan46/Qwen3.5-35B-A3B-uncensored-heretic" \
        --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": "llmfan46/Qwen3.5-35B-A3B-uncensored-heretic",
		"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 llmfan46/Qwen3.5-35B-A3B-uncensored-heretic with Docker Model Runner:
```
docker model run hf.co/llmfan46/Qwen3.5-35B-A3B-uncensored-heretic
```

GGUF version request (Q4_K_M / Q4_K_S)

by Nuke1229 - opened Feb 27

Discussion

Nuke1229

Feb 27

Could you please provide a GGUF version of this model? I'd be happy with either Q4_K_M or Q4_K_S quantization. Thank you.

llmfan46

Owner Feb 27

Could you please provide a GGUF version of this model? I'd be happy with either Q4_K_M or Q4_K_S quantization. Thank you.

https://huggingface.co/llmfan46/Qwen3.5-35B-A3B-heretic-GGUF

Noire1

Mar 2

Could you please provide a GGUF version of this model? I'd be happy with either Q4_K_M or Q4_K_S quantization. Thank you.

Could you please provide a GGUF version of this model? I'd be happy with either Q4_K_M or Q4_K_S quantization. Thank you.

https://huggingface.co/llmfan46/Qwen3.5-35B-A3B-heretic-GGUF

Really good, I'm using Q5.
@llmfan46 Thank you.

@Nuke1229 I must thank you so much, it is actually really good. I was testing it with several images, it follows the system instruction very well. Some times it captions the poses wrong, some times it mentions a genital that is not visible but still better than other uncensored version from other author imo.
I'm using KoboldCPP and I'm not sure if my template is correct or not or if can improve even more but its working nice.

Nuke1229

Mar 2

•

edited Mar 2

@Nuke1229 I must thank you so much, it is actually really good. I was testing it with several images, it follows the system instruction very well. Some times it captions the poses wrong, some times it mentions a genital that is not visible but still better than other uncensored version from other author imo.
I'm using KoboldCPP and I'm not sure if my template is correct or not or if can improve even more but its working nice.

@Noire1 I use jan.ai, so I’m not entirely sure, but if you’re doing NSFW captions, I recommend running the images through a tagger first. Then, feed both the tags and the image into the LLM. Use the tags as a guide and reinforce it in the system prompt with something like: "Analyze the image and write a description based on these tags, but use your own judgment and verify if the tags are accurate."

To be honest, the system prompt needs to be longer and more detailed. For genitals or small details, you should use 'leading' instructions—hinting that 'there might be [X] present, so look closely.' This forces the model to increase its inference time (thinking time) and focus its attention more effectively.

Noire1

Mar 3

@Nuke1229 I must thank you so much, it is actually really good. I was testing it with several images, it follows the system instruction very well. Some times it captions the poses wrong, some times it mentions a genital that is not visible but still better than other uncensored version from other author imo.
I'm using KoboldCPP and I'm not sure if my template is correct or not or if can improve even more but its working nice.

@Noire1 I use jan.ai, so I’m not entirely sure, but if you’re doing NSFW captions, I recommend running the images through a tagger first. Then, feed both the tags and the image into the LLM. Use the tags as a guide and reinforce it in the system prompt with something like: "Analyze the image and write a description based on these tags, but use your own judgment and verify if the tags are accurate."

To be honest, the system prompt needs to be longer and more detailed. For genitals or small details, you should use 'leading' instructions—hinting that 'there might be [X] present, so look closely.' This forces the model to increase its inference time (thinking time) and focus its attention more effectively.

@Nuke1229 Thank you, I'm using Jan.Ai for the first time and I'm impressed, the quality is even better than KoboldCPP!!!

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