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Model: prithivMLmods/Qwen2.5-VL-3B-Instruct-Unredacted-MAX Source: Original Platform
2026-06-04 00:30:12 +08:00
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+---
+license: apache-2.0
+base_model:
+- Qwen/Qwen2.5-VL-3B-Instruct
+tags:
+- text-generation-inference
+- uncensored
+- abliterated
+- unfiltered
+- unredacted
+- vllm
+- pytorch
+- BF16
+- max
+- legal
+language:
+- en
+pipeline_tag: image-text-to-text
+library_name: transformers
+---
+
+![1](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/3qvAAEbqHKQviJuKfurJB.png)
+
+# **Qwen2.5-VL-3B-Instruct-Unredacted-MAX**
+
+> **Qwen2.5-VL-3B-Instruct-Unredacted-MAX** is an optimized release built on top of **huihui-ai/Qwen2.5-VL-3B-Instruct-abliterated**. This version focuses on **improved model packaging, updated compatibility with modern Transformers pipelines, and stable multimodal inference behavior**, while preserving the core vision-language reasoning capabilities of the original architecture. The result is a compact **3B vision-language model** designed for efficient deployment, research experimentation, and multimodal application development.
+
+## Key Highlights
+
+* **Optimized Release Packaging**
+  Streamlined repository structure for smoother loading, inference, and deployment workflows.
+
+* **Modern Transformers Compatibility**
+  Updated to ensure stable integration with recent Hugging Face Transformers versions.
+
+* **3B Vision-Language Architecture**
+  Built on **Qwen2.5-VL-3B-Instruct**, balancing multimodal capability with lightweight deployment requirements.
+
+* **Stable Multimodal Inference**
+  Designed for consistent performance across image-text reasoning tasks.
+
+* **Efficient Caption Generation**
+  Produces structured, descriptive outputs suitable for annotation and dataset building.
+
+* **Dynamic Resolution Support**
+  Retains native handling of varying image resolutions and aspect ratios.
+
+---
+
+## Base Model Signatures:
+
+This model has been re-sharded and optimized for the latest Transformers version from the base model:
+https://huggingface.co/huihui-ai/Qwen2.5-VL-3B-Instruct-abliterated
+
+---
+
+## Quick Start with Transformers
+
+```python id="vl3b_code"
+from transformers import Qwen2_5_VLForConditionalGeneration, AutoTokenizer, AutoProcessor
+from qwen_vl_utils import process_vision_info
+import torch
+
+model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
+    "prithivMLmods/Qwen2.5-VL-3B-Instruct-Unredacted-MAX",
+    torch_dtype="auto",
+    device_map="auto"
+)
+
+processor = AutoProcessor.from_pretrained(
+    "prithivMLmods/Qwen2.5-VL-3B-Instruct-Unredacted-MAX"
+)
+
+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 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=256)
+
+output_text = processor.batch_decode(
+    [out[len(inp):] for inp, out in zip(inputs.input_ids, generated_ids)],
+    skip_special_tokens=True,
+    clean_up_tokenization_spaces=False
+)
+
+print(output_text)
+```
+
+---
+
+## Intended Use
+
+* Multimodal AI research and evaluation
+* Image captioning and dataset generation pipelines
+* Vision-language prototyping and experimentation
+* Lightweight deployment in constrained environments
+* Development of multimodal applications and tools
+
+---
+
+## Limitations & Risks
+
+> **Important Note**: This model inherits behavior and constraints from its base architecture.
+
+* Performance depends on image quality, resolution, and prompt design
+* May produce incomplete or inaccurate interpretations in complex scenes
+* Requires adequate GPU resources for stable inference
+* Output consistency varies with decoding settings and runtime optimization