PrunaAI
/

P-Q-Image-2.1

@@ -1,6 +1,5 @@
 ---
-## license: other
 license_name: qwen-research
 base_model: Qwen/Qwen-Image-2.1
 library_name: diffusers
@@ -13,25 +12,55 @@ tags:
   - lora
   - distilled
   - few-step
-![](assets/Pruna-Q-Image-2.1.png)
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gMzQ1LjMyOGMuODk5LS4yNCAyLjgwMS0uMTk3IDYuMzA0LjQ2NCA2LjMxMSAxLjE5IDE2LjU4NSA0LjIyMSAyNi4xMjIgNC4yMjEgOS40NTIgMCAxNy4xMTgtMS45MjYgMjEuMzgzLTIuNjAzLjc3LS4xMjMgMS4zODUtLjE5OSAxLjg3OC0uMjM3LS4zNCAxMy44NDMtMTIuODkzIDI3LjcxLTI3Ljg2OCAyNy43MS0xNS4xNzIgMC0yNy44NzYtMTMuODM1LTI3Ljg3Ni0yOC44MTEgMC0uMzU3LjAyOS0uNTk2LjA1Ny0uNzQ0WiIvPjwvc3ZnPg==)
-# ⚡ Pruna-Q-Image-2.1
-## Few-step LoRA adapters for Qwen-Image-2.1
-### 6 steps (v0.2), 5 or 8 steps (v0.1)  ·  Up to 6.3x faster  ·  No CFG  ·  Text-to-image and image editing
-**Pruna-Q-Image-2.1 is a set of LoRA adapters that let**
-`[Qwen/Qwen-Image-2.1](https://huggingface.co/Qwen/Qwen-Image-2.1)` **generate
 and edit images in only 6 steps (v0.2), or 5 or 8 steps (v0.1). The adapters load on top of the base
 model, so the pipeline, text encoder, and VAE stay unchanged. Training is based
 on DMD.**
@@ -44,23 +73,17 @@ on DMD.**
 > visual quality of the base model. We are still improving the distillation and
 > will update this repository as new versions become available.
 ## Variants
 ### v0.2
 Pick **basic** for faithful base-model behavior, or **prompt-upsampled** for
 improved visual quality from a short prompt.
-| File                                               | Steps | Trade-off                                                                                      |
-| -------------------------------------------------- | ----- | ---------------------------------------------------------------------------------------------- |
-| `p_q_image_2.1_basic_6_steps_v0.2.safetensors`     | 6     | **Pure few-step distillation.** Recommended for preserving inputs when editing.                |
-| `p_q_image_2.1_upsampled_6_steps_v0.2.safetensors` | 6     | **Improved visual quality.** A first attempt at distilling prompt upsampling into the adapter. |
 **Basic** is a pure 6-step distillation of the base model, without any additional
 post-training. It is intended as a drop-in replacement for the base model in
@@ -77,12 +100,10 @@ what the actual prompt upsampler would do, and we will continue improving it.
 Both adapters are v0.1. Pick one based on whether you need **quality** or **speed**.
-| File                                   | Steps | Trade-off                                               |
-| -------------------------------------- | ----- | ------------------------------------------------------- |
-| `p_q_image_2.1_8step_v0.1.safetensors` | 8     | **Higher quality.** Recommended as the default.         |
-| `p_q_image_2.1_5step_v0.1.safetensors` | 5     | **Higher speed**, with noticeably lower visual quality. |
 Each adapter is trained for its own sigma schedule. Load only one at a time.
 For the v0.2 adapters, do not reuse the v0.1 schedules.
@@ -108,16 +129,20 @@ inference speed, not a guarantee of quality at that resolution.
 ## Benchmarking
 ### v0.2: 6-step LoRA and prompt upsampling
-|                                                                                                                         |
-| ----------------------------------------------------------------------------------------------------------------------- |
-| ![Six-step generation latency at 1024 and 2048 pixels](assets/Pruna-Q-Image-2.1-v02-generation.png)                     |
-| ![Prompt-upsampling latency for text and one to three reference images](assets/Pruna-Q-Image-2.1-prompt-upsampling.png) |
 One NVIDIA H100 80GB per worker, BF16, batch size 1. Median of 3 requests after
 one warmup per configuration, with seed 42. Wall-clock time is measured around
@@ -128,8 +153,8 @@ adapter loading, warmup, fixture preparation, file saving, and network transport
 No CFG, compilation, CPU offload, or diffusion KV caching.
 Prompt upsampling is measured separately using
-`[Qwen-Image-2.1-PE-T2I](https://huggingface.co/Qwen/Qwen-Image-2.1-PE-T2I)`
-and `[Qwen-Image-2.1-PE-I2I](https://huggingface.co/Qwen/Qwen-Image-2.1-PE-I2I)`,
 with their task-specific sampling settings and thinking enabled. Timing includes
 request preparation from in-memory images, image and text processing, text
 generation, and response parsing. It does not include image generation. The
@@ -164,11 +189,24 @@ No requests are silently retried.
 ### v0.1
-|                                            |                                            |
-| ------------------------------------------ | ------------------------------------------ |
-| ![](assets/Pruna-Q-Image-2.1-t2i-1024.png) | ![](assets/Pruna-Q-Image-2.1-t2i-2048.png) |
-| ![](assets/Pruna-Q-Image-2.1-i2i-1024.png) | ![](assets/Pruna-Q-Image-2.1-i2i-2048.png) |
 Text-to-image with the official Qwen model-card example prompt, BF16, batch size 1,
 on one NVIDIA H100 80GB. Median of 3 requests after one warmup per configuration.
@@ -187,8 +225,6 @@ pip install 'torch>=2.4.0' 'transformers>=5.17' accelerate peft pillow
 pip install git+https://github.com/huggingface/diffusers@6256aa7666cedd47443adc8f82da9a10e110b09c
 ```
 ### v0.2
 Use this setup for either v0.2 adapter.
@@ -224,7 +260,8 @@ pipe.scheduler = FlowMatchEulerDiscreteScheduler.from_config(
 )
 ```
-Both variants load on `Qwen/Qwen-Image-2.1` using `QwenImage21Pipeline`.
 Choose one LoRA with `VARIANT`; the prompt-upsampled variant runs directly on your
 original prompt without a separate prompt-enhancer model. For a local export,
 replace `"PrunaAI/Pruna-Q-Image-2.1"` with the folder containing the chosen
@@ -269,8 +306,6 @@ pipe.scheduler = FlowMatchEulerDiscreteScheduler.from_config(
 )
 ```
 ## For Text-to-Image
 Longer, more descriptive prompts give better results.
@@ -292,8 +327,6 @@ image = pipe(
 ).images[0]
 ```
 ### For Image Editing
 ```python
@@ -308,8 +341,6 @@ image = pipe(
 ).images[0]
 ```
 ### Recommended settings
 For **v0.2**, use the unshifted six-step sigmas
@@ -320,43 +351,35 @@ terminal zero. Keep `true_cfg_scale=1.0` and LoRA strength 1.0.
 The **v0.1** settings are:
 - **Use the sigma schedule that matches your adapter**, and keep the scheduler
-at `shift=1.0` with dynamic shifting off so the sigmas are not shifted twice.
   - 8-step: `1 → 14/15 → 6/7 → 10/13 → 2/3 → 6/11 → 0.4 → 2/9 → 0`
-  (shift 2, computed as `σ = 2t / (1 + t)` on evenly spaced `t`)
   - 5-step: `1 → 0.94 → 6/7 → 2/3 → 0.4 → 0`
 - **No CFG.** Keep `true_cfg_scale=1.0` and do not pass a negative prompt.
 - **Keep the LoRA strength at 1.0.**
 - **Write detailed prompts for text-to-image.** Longer prompts that describe
-the subject, setting, lighting, and style work noticeably better than short
-ones.
 ## Limitations
 ### v0.2
 - The prompt-upsampled adapter is a first attempt. It can improve visual quality,
-but may not exactly reproduce the output of the actual prompt upsampler.
 - Basic is intended to preserve the base model's behavior in fewer steps;
-distillation does not guarantee identical outputs.
 - Use the step count and sigma schedule that match your v0.2 adapter. Other step
-counts, schedules, or CFG values are not supported.
 ### v0.1
 - This is a first version. Quality is below that of the base model.
 - The 5-step adapter is faster than the 8-step one, but its images are
-visibly worse.
 - Short or vague text-to-image prompts give weaker results.
 - The adapters are only intended for the settings above. Other step counts,
-schedules, or CFG values are not supported.
 ## What this is not
@@ -364,8 +387,6 @@ schedules, or CFG values are not supported.
 - Not a replacement for the base model when you need its full quality.
 - Not a finished release. Expect the weights to change in future versions.
 ## License
 The end distilled model is based on Qwen-Image-2.1.
@@ -383,6 +404,32 @@ Hangzhou Tongyi Laboratory Technology Co., Ltd. All Rights Reserved.
 - Compress your own models with [Pruna](https://github.com/PrunaAI/pruna) and give us a ⭐️ for more efficiency!
 - Want to use our optimized image models right away?  Check [P-Image-Ideogram](https://www.pruna.ai/p-image-ideogram) and [P-Image-Edit](https://www.pruna.ai/p-image-edit).
-[Try our models](https://dashboard.pruna.ai/login?utm_source=huggingface&utm_medium=model_card&utm_campaign=hf_traffic)

 ---
+license: other
 license_name: qwen-research
 base_model: Qwen/Qwen-Image-2.1
 library_name: diffusers
   - lora
   - distilled
   - few-step
+---
+<!-- header start -->
+<!-- 200823 -->
+<p align="center">
+  <img src="assets/Pruna-Q-Image-2.1.png" width="800">
+</p>
+<!-- header end -->
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+  <a href="https://dashboard.pruna.ai/login?utm_source=huggingface&utm_medium=org_card&utm_campaign=hf_traffic">
+    <img src="https://img.shields.io/badge/Performance%20Models-Try%20them%20now-9334E9?style=plastic&logo=data:image/svg%2bxml;base64,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" alt="Performance Models">
+  </a>
+</p>
+<div align="center">
+<h1 style="color: #9334E9;">⚡ Pruna-Q-Image-2.1</h1>
+<h2>Few-step LoRA adapters for Qwen-Image-2.1</h2>
+<h3>
+  <span style="color: #9334E9;">6 steps (v0.2), 5 or 8 steps (v0.1)</span>
+  &nbsp;·&nbsp;
+  <span style="color: #9334E9;">Up to 6.3x faster</span>
+  &nbsp;·&nbsp;
+  <span style="color: #9334E9;">No CFG</span>
+  &nbsp;·&nbsp;
+  Text-to-image and image editing
+</h3>
+</div>
+**Pruna-Q-Image-2.1 is a set of LoRA adapters that let
+[`Qwen/Qwen-Image-2.1`](https://huggingface.co/Qwen/Qwen-Image-2.1) generate
 and edit images in only 6 steps (v0.2), or 5 or 8 steps (v0.1). The adapters load on top of the base
 model, so the pipeline, text encoder, and VAE stay unchanged. Training is based
 on DMD.**
 > visual quality of the base model. We are still improving the distillation and
 > will update this repository as new versions become available.
 ## Variants
 ### v0.2
 Pick **basic** for faithful base-model behavior, or **prompt-upsampled** for
 improved visual quality from a short prompt.
+| File | Steps | Trade-off |
+|---|:---:|---|
+| `p_q_image_2.1_basic_6_steps_v0.2.safetensors` | 6 | **Pure few-step distillation.** Recommended for preserving inputs when editing. |
+| `p_q_image_2.1_upsampled_6_steps_v0.2.safetensors` | 6 | **Improved visual quality.** A first attempt at distilling prompt upsampling into the adapter. |
 **Basic** is a pure 6-step distillation of the base model, without any additional
 post-training. It is intended as a drop-in replacement for the base model in
 Both adapters are v0.1. Pick one based on whether you need **quality** or **speed**.
+| File | Steps | Trade-off |
+|---|:---:|---|
+| `p_q_image_2.1_8step_v0.1.safetensors` | 8 | **Higher quality.** Recommended as the default. |
+| `p_q_image_2.1_5step_v0.1.safetensors` | 5 | **Higher speed**, with noticeably lower visual quality. |
 Each adapter is trained for its own sigma schedule. Load only one at a time.
 For the v0.2 adapters, do not reuse the v0.1 schedules.
 ## Benchmarking
 ### v0.2: 6-step LoRA and prompt upsampling
+<table>
+  <tr>
+    <td>
+      <img src="assets/Pruna-Q-Image-2.1-v02-generation.png" alt="Six-step generation latency at 1024 and 2048 pixels" width="100%">
+    </td>
+  </tr>
+  <tr>
+    <td>
+      <img src="assets/Pruna-Q-Image-2.1-prompt-upsampling.png" alt="Prompt-upsampling latency for text and one to three reference images" width="100%">
+    </td>
+  </tr>
+</table>
 One NVIDIA H100 80GB per worker, BF16, batch size 1. Median of 3 requests after
 one warmup per configuration, with seed 42. Wall-clock time is measured around
 No CFG, compilation, CPU offload, or diffusion KV caching.
 Prompt upsampling is measured separately using
+[`Qwen-Image-2.1-PE-T2I`](https://huggingface.co/Qwen/Qwen-Image-2.1-PE-T2I)
+and [`Qwen-Image-2.1-PE-I2I`](https://huggingface.co/Qwen/Qwen-Image-2.1-PE-I2I),
 with their task-specific sampling settings and thinking enabled. Timing includes
 request preparation from in-memory images, image and text processing, text
 generation, and response parsing. It does not include image generation. The
 ### v0.1
+<table>
+  <tr>
+    <td width="50%">
+      <img src="assets/Pruna-Q-Image-2.1-t2i-1024.png" width="100%">
+    </td>
+    <td width="50%">
+      <img src="assets/Pruna-Q-Image-2.1-t2i-2048.png" width="100%">
+    </td>
+  </tr>
+  <tr>
+    <td width="50%">
+      <img src="assets/Pruna-Q-Image-2.1-i2i-1024.png" width="100%">
+    </td>
+    <td width="50%">
+      <img src="assets/Pruna-Q-Image-2.1-i2i-2048.png" width="100%">
+    </td>
+  </tr>
+</table>
 Text-to-image with the official Qwen model-card example prompt, BF16, batch size 1,
 on one NVIDIA H100 80GB. Median of 3 requests after one warmup per configuration.
 pip install git+https://github.com/huggingface/diffusers@6256aa7666cedd47443adc8f82da9a10e110b09c
 ```
 ### v0.2
 Use this setup for either v0.2 adapter.
 )
 ```
+Both variants load on **`Qwen/Qwen-Image-2.1`** using **`QwenImage21Pipeline`**.
 Choose one LoRA with `VARIANT`; the prompt-upsampled variant runs directly on your
 original prompt without a separate prompt-enhancer model. For a local export,
 replace `"PrunaAI/Pruna-Q-Image-2.1"` with the folder containing the chosen
 )
 ```
 ## For Text-to-Image
 Longer, more descriptive prompts give better results.
 ).images[0]
 ```
 ### For Image Editing
 ```python
 ).images[0]
 ```
 ### Recommended settings
 For **v0.2**, use the unshifted six-step sigmas
 The **v0.1** settings are:
 - **Use the sigma schedule that matches your adapter**, and keep the scheduler
+  at `shift=1.0` with dynamic shifting off so the sigmas are not shifted twice.
   - 8-step: `1 → 14/15 → 6/7 → 10/13 → 2/3 → 6/11 → 0.4 → 2/9 → 0`
+    (shift 2, computed as `σ = 2t / (1 + t)` on evenly spaced `t`)
   - 5-step: `1 → 0.94 → 6/7 → 2/3 → 0.4 → 0`
 - **No CFG.** Keep `true_cfg_scale=1.0` and do not pass a negative prompt.
 - **Keep the LoRA strength at 1.0.**
 - **Write detailed prompts for text-to-image.** Longer prompts that describe
+  the subject, setting, lighting, and style work noticeably better than short
+  ones.
 ## Limitations
 ### v0.2
 - The prompt-upsampled adapter is a first attempt. It can improve visual quality,
+  but may not exactly reproduce the output of the actual prompt upsampler.
 - Basic is intended to preserve the base model's behavior in fewer steps;
+  distillation does not guarantee identical outputs.
 - Use the step count and sigma schedule that match your v0.2 adapter. Other step
+  counts, schedules, or CFG values are not supported.
 ### v0.1
 - This is a first version. Quality is below that of the base model.
 - The 5-step adapter is faster than the 8-step one, but its images are
+  visibly worse.
 - Short or vague text-to-image prompts give weaker results.
 - The adapters are only intended for the settings above. Other step counts,
+  schedules, or CFG values are not supported.
 ## What this is not
 - Not a replacement for the base model when you need its full quality.
 - Not a finished release. Expect the weights to change in future versions.
 ## License
 The end distilled model is based on Qwen-Image-2.1.
 - Compress your own models with [Pruna](https://github.com/PrunaAI/pruna) and give us a ⭐️ for more efficiency!
 - Want to use our optimized image models right away?  Check [P-Image-Ideogram](https://www.pruna.ai/p-image-ideogram) and [P-Image-Edit](https://www.pruna.ai/p-image-edit).
+<style>
+.model-button {
+  display: inline-flex;
+  flex-direction: row;
+  justify-content: center;
+  align-items: center;
+  gap: 8px;
+  padding: 8px 20px;
+  border: none;
+  border-radius: 8px;
+  background: #9334e9;
+  color: #ffffff;
+  font-size: 14px;
+  font-weight: 400;
+  line-height: 1;
+  text-decoration: none;
+  white-space: nowrap;
+  cursor: pointer;
+  box-sizing: border-box;
+  overflow: visible;
+  opacity: 1;
+}
+</style>
+<a href="https://dashboard.pruna.ai/login?utm_source=huggingface&utm_medium=model_card&utm_campaign=hf_traffic" class="model-button">Try our models</a>