Image-Text-to-Text
Transformers
Safetensors
qwen3_5
qwen3.8
conversational
comfyui
fine-tuned
sft
unsloth
vision-language
mtp
Instructions to use Rom3rk/Qwen3.8-27B-ComfyUI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rom3rk/Qwen3.8-27B-ComfyUI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Rom3rk/Qwen3.8-27B-ComfyUI") 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("Rom3rk/Qwen3.8-27B-ComfyUI") model = AutoModelForMultimodalLM.from_pretrained("Rom3rk/Qwen3.8-27B-ComfyUI", 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 Rom3rk/Qwen3.8-27B-ComfyUI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Rom3rk/Qwen3.8-27B-ComfyUI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Rom3rk/Qwen3.8-27B-ComfyUI", "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/Rom3rk/Qwen3.8-27B-ComfyUI
- SGLang
How to use Rom3rk/Qwen3.8-27B-ComfyUI 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 "Rom3rk/Qwen3.8-27B-ComfyUI" \ --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": "Rom3rk/Qwen3.8-27B-ComfyUI", "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 "Rom3rk/Qwen3.8-27B-ComfyUI" \ --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": "Rom3rk/Qwen3.8-27B-ComfyUI", "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" } } ] } ] }' - Unsloth Desktop
- Docker Model Runner
How to use Rom3rk/Qwen3.8-27B-ComfyUI with Docker Model Runner:
docker model run hf.co/Rom3rk/Qwen3.8-27B-ComfyUI
File size: 4,990 Bytes
ace58f4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 | ---
base_model:
- Qwen/Qwen3.8-27B
base_model_relation: finetune
license: apache-2.0
library_name: transformers
pipeline_tag: image-text-to-text
tags:
- transformers
- safetensors
- qwen3.8
- conversational
- comfyui
- fine-tuned
- sft
- unsloth
- vision-language
- mtp
---
# Qwen3.8-27B-ComfyUI
Qwen3.8-27B-ComfyUI is a fine-tuned Qwen3.8-27B model specialized for generating, editing, repairing, auditing, and explaining ComfyUI frontend/UI workflow JSON.
## Overview
```text
ComfyUI request
-> interpret workflow intent and constraints
-> generate, edit, repair, audit, or explain
-> return workflow JSON or a conversational answer
```
## Capabilities
- Generate ComfyUI UI workflows from natural-language requests
- Edit existing workflows while preserving requested components
- Repair invalid, incomplete, or disconnected workflows
- Audit workflow structure, nodes, inputs, and links
- Explain workflow behavior and node interactions
- Provide raw workflow JSON or conversational ComfyUI assistance
## Quick Start
Install the required libraries:
```bash
pip install --upgrade transformers accelerate safetensors
```
```python
import torch
from transformers import AutoModelForImageTextToText, AutoProcessor
MODEL_ID = "Rom3rk/Qwen3.8-27B-ComfyUI"
ENABLE_THINKING = False
processor = AutoProcessor.from_pretrained(MODEL_ID)
model = AutoModelForImageTextToText.from_pretrained(
MODEL_ID,
dtype=torch.bfloat16,
device_map="auto",
).eval()
messages = [
{
"role": "user",
"content": [
{
"type": "text",
"text": (
"Create a ComfyUI UI workflow for an SDXL image-to-image "
"pipeline with a ControlNet depth branch and return the "
"complete loadable UI workflow JSON."
),
}
],
}
]
inputs = processor.apply_chat_template(
messages,
tokenize=True,
add_generation_prompt=True,
enable_thinking=ENABLE_THINKING,
return_dict=True,
return_tensors="pt",
).to(model.device)
with torch.inference_mode():
generated_ids = model.generate(
**inputs,
max_new_tokens=4096,
do_sample=True,
temperature=0.7,
top_p=0.8,
top_k=20,
)
new_tokens = generated_ids[:, inputs.input_ids.shape[1]:]
response = processor.batch_decode(
new_tokens,
skip_special_tokens=True,
clean_up_tokenization_spaces=False,
)[0]
print(response)
```
The model uses Qwen's native chat template. Set `ENABLE_THINKING` according to the task and inference runtime rather than replacing the template.
## Usage Examples
### Workflow Generation
```text
Create a ComfyUI UI workflow for an SDXL image-to-image pipeline with a ControlNet depth branch, a two-stage sampler, and a final image-save node. Return the complete loadable UI workflow JSON.
```
### Workflow Editing
```text
Modify the following ComfyUI UI workflow to add a second ControlNet branch. Preserve the existing model, sampler settings, node positions, and unrelated links.
```
### Workflow Repair
```text
Repair the invalid links and missing required inputs in this ComfyUI UI workflow. Keep all valid nodes and settings unchanged, and return the corrected workflow JSON.
```
### Workflow Audit
```text
Audit this ComfyUI UI workflow for invalid endpoints, disconnected nodes, incompatible inputs, redundant components, and settings that conflict with the requested generation pipeline.
```
## Recommended Sampling Settings
| Mode | Temperature | Top-p | Top-k | Presence penalty |
|---|---:|---:|---:|---:|
| Thinking | 1.0 | 0.95 | 20 | 0.0 |
| Non-thinking | 0.7 | 0.80 | 20 | 1.5 |
These settings follow the recommendations published for Qwen3.8. Availability and parameter names may vary by inference runtime.
## Questions and Feedback
For questions, bug reports, workflow compatibility issues, or general feedback, please open a Discussion from this repository's **Community** tab.
When reporting a workflow issue, please include:
- Inference runtime and version
- ComfyUI version
- Relevant custom nodes
- The original prompt
- The generated workflow JSON or raw model output
## License and Attribution
This model is a modified derivative of [Qwen/Qwen3.8-27B](https://huggingface.co/Qwen/Qwen3.8-27B) and is distributed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). See the repository's `LICENSE` file for the full license text.
Qwen3.8 was developed by the Qwen Team. Model fine-tuning and merging used [Unsloth](https://unsloth.ai/).
## Citation
```bibtex
@misc{qwen38,
title = {{Qwen3.8-Max}: A New Bar for Coding and Cowork},
author = {{Qwen Team}},
month = {August},
year = {2026},
url = {https://qwen.ai/blog?id=qwen3.8}
}
```
## References
- [Qwen3.8-27B](https://huggingface.co/Qwen/Qwen3.8-27B)
- [Unsloth](https://unsloth.ai/)
- [Transformers](https://huggingface.co/docs/transformers/)
|