---
license: apache-2.0
base_model:
- Qwen/Qwen3-VL-8B-Thinking
language:
- en
pipeline_tag: image-text-to-text
library_name: transformers
tags:
- text-generation-inference
- abliterated
- v1.0
---

![1](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/_bWMf39GbBfbi1CktwneH.png)

# **Qwen3-VL-8B-Thinking-abliterated**

> **Qwen3-VL-8B-Thinking-abliterated** is an abliterated (v1.0) variant of Qwen3-VL-8B-Thinking, designed for Abliterated Reasoning and Captioning.
> This model produces detailed captions and reasoning outputs across a wide range of visual and multimodal contexts, including complex, sensitive, or nuanced content. It supports diverse aspect ratios, resolutions, and prompt conditions while maintaining reasoning integrity and descriptive precision.

<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/1xWD8FQ2qvqQzyqOzy05I.jpeg" alt="1" style="border-radius: 30px;"/>

## Key Highlights

* **Abliterated / Uncensored Captioning**
  Fine-tuned to bypass conventional content filters while preserving factual, descriptive, and reasoning-rich outputs.

* **High-Fidelity Reasoning and Descriptions**
  Generates comprehensive captions and reasoning for general, artistic, technical, abstract, and low-context images.

* **Robust Across Aspect Ratios**
  Performs consistently on wide, tall, square, panoramic, and irregular image dimensions.

* **Variational Detail Control**
  Produces outputs ranging from concise summaries to fine-grained, high-context reasoning and descriptions.

* **Foundation on Qwen3-VL-8B-Thinking Architecture**
  Built upon the Qwen3-VL-8B-Thinking model’s advanced multimodal reasoning and instruction-following capabilities.

* **Multilingual Output Capability**
  Defaults to English but can be adapted to other languages via prompt engineering.

## Quick Start with Transformers

```python
from transformers import Qwen3VLForConditionalGeneration, AutoProcessor
from qwen_vl_utils import process_vision_info
import torch

model = Qwen3VLForConditionalGeneration.from_pretrained(
    "prithivMLmods/Qwen3-VL-8B-Thinking-abliterated",
    torch_dtype="auto",
    device_map="auto"
)

processor = AutoProcessor.from_pretrained("prithivMLmods/Qwen3-VL-8B-Thinking-abliterated")

messages = [
    {
        "role": "user",
        "content": [
            {
                "type": "image",
                "image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg",
            },
            {"type": "text", "text": "Provide a detailed caption and reasoning for this image."},
        ],
    }
]

text = processor.apply_chat_template(
    messages, tokenize=False, add_generation_prompt=True
)
image_inputs, video_inputs = process_vision_info(messages)

inputs = processor(
    text=[text],
    images=image_inputs,
    videos=video_inputs,
    padding=True,
    return_tensors="pt",
).to("cuda")

generated_ids = model.generate(**inputs, max_new_tokens=128)

generated_ids_trimmed = [
    out_ids[len(in_ids):] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
]

output_text = processor.batch_decode(
    generated_ids_trimmed,
    skip_special_tokens=True,
    clean_up_tokenization_spaces=False
)

print(output_text)
```

## Intended Use

This model is suited for:

* Generating detailed, uncensored captions and reasoning for general-purpose, artistic, or research-oriented datasets.
* Research in content moderation, red-teaming, and generative safety analysis.
* Enabling descriptive captioning and reasoning for datasets typically excluded from mainstream models.
* Creative applications such as visual storytelling, art description, and multimodal reasoning exploration.
* Captioning and reasoning for images with non-standard or stylized visual structures.

## Limitations

* May generate explicit, sensitive, or offensive content depending on prompts and image input.
* Not suitable for production systems that require strict content moderation.
* Output style, tone, and reasoning depth may vary based on input phrasing.
* Accuracy may fluctuate for abstract, synthetic, or highly stylized visuals.