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

Libraries

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

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

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

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "trohrbaugh/Qwen3.5-35B-A3B-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": "trohrbaugh/Qwen3.5-35B-A3B-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/trohrbaugh/Qwen3.5-35B-A3B-heretic

SGLang

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

trohrbaugh commited on May 2

Commit

b9697c2

verified ·

1 Parent(s): aad1954

aux-rescue: add banner (785 tensors)

Browse files

Files changed (1) hide show

README.md +24 -0

README.md CHANGED Viewed

@@ -11,6 +11,30 @@ tags:
 - decensored
 - abliterated
 ---
 # This is a decensored version of [Qwen/Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0
 ## Abliteration parameters

 - decensored
 - abliterated
 ---
+<!-- aux-rescue-banner: begin -->
+> ## ⚠️ Update 2026-05-02 — please re-pull this model
+>
+> An earlier upload of this repo was missing `mtp.*` weights
+> (785 tensors) due to a bug in `save_pretrained`: tensors not
+> registered in the loaded model class's `state_dict()` were silently
+> dropped on save.
+>
+> **Symptom:** vLLM speculative decoding with `--speculative-config qwen3_next_mtp` would fail to load. Regular (non-spec-decoded) inference and image-text-to-text were unaffected.
+>
+> **Status:** fixed on 2026-05-02 by uploading `model-auxiliary.safetensors` and
+> patching `model.safetensors.index.json`. The repo now carries an
+> `.aux_rescue.json` marker file so this fact is programmatically
+> verifiable.
+>
+> Source used for restoration: [`Qwen/Qwen3.5-35B-A3B`](https://huggingface.co/Qwen/Qwen3.5-35B-A3B)
+>
+> If you cloned this repo before 2026-05-02, please pull again.
+> Repaired with [`aux-rescue`](https://github.com/timrohrbaugh/aux-rescue).
+<!-- aux-rescue-banner: end -->
 # This is a decensored version of [Qwen/Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0
 ## Abliteration parameters