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.gitattributes

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+demo.jpg filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,105 @@
+---
+license: mit
+tags:
+- image-generation
+- HiDream.ai
+language:
+- en
+pipeline_tag: text-to-image
+library_name: diffusers
+---
+
+![HiDream-I1 Demo](demo.jpg)
+
+`HiDream-I1` is a new open-source image generative foundation model with 17B parameters that achieves state-of-the-art image generation quality within seconds.
+
+<span style="color: #FF5733; font-weight: bold">For more features and to experience the full capabilities of our product, please visit [https://vivago.ai/](https://vivago.ai/).</span>
+
+## Key Features
+- ✨ **Superior Image Quality** - Produces exceptional results across multiple styles including photorealistic, cartoon, artistic, and more. Achieves state-of-the-art HPS v2.1 score, which aligns with human preferences.
+- 🎯 **Best-in-Class Prompt Following** - Achieves industry-leading scores on GenEval and DPG benchmarks, outperforming all other open-source models.
+- 🔓 **Open Source** - Released under the MIT license to foster scientific advancement and enable creative innovation.
+- 💼 **Commercial-Friendly** - Generated images can be freely used for personal projects, scientific research, and commercial applications.
+
+## Quick Start
+Please make sure you have installed [Flash Attention](https://github.com/Dao-AILab/flash-attention). We recommend CUDA version 12.4 for the manual installation.
+```
+pip install -r requirements.txt
+```
+Clone the GitHub repo:
+```
+git clone https://github.com/HiDream-ai/HiDream-I1
+```
+
+Then you can run the inference scripts to generate images:
+
+```python
+# For full model inference
+python ./inference.py --model_type full
+
+# For distilled dev model inference
+python ./inference.py --model_type dev
+
+# For distilled fast model inference
+python ./inference.py --model_type fast
+```
+> **Note:** The inference script will automatically download `meta-llama/Meta-Llama-3.1-8B-Instruct` model files. If you encounter network issues, you can download these files ahead of time and place them in the appropriate cache directory to avoid download failures during inference.
+
+## Gradio Demo
+
+We also provide a Gradio demo for interactive image generation. You can run the demo with:
+
+```python
+python gradio_demo.py 
+```
+
+## Evaluation Metrics
+
+### DPG-Bench
+| Model           | Overall   | Global    | Entity    | Attribute | Relation  | Other     |
+|-----------------|-----------|-----------|-----------|-----------|-----------|-----------|
+| PixArt-alpha    |    71.11  | 74.97     | 79.32     | 78.60     | 82.57     | 76.96     |
+| SDXL            |    74.65  | 83.27     | 82.43     | 80.91     | 86.76     | 80.41     |
+| DALL-E 3        |    83.50  | 90.97     | 89.61     | 88.39     | 90.58     | 89.83     |
+| Flux.1-dev      |    83.79  | 85.80     | 86.79     | 89.98     | 90.04     | 89.90     |
+| SD3-Medium      |    84.08  | 87.90     | 91.01     | 88.83     | 80.70     | 88.68     |
+| Janus-Pro-7B    |    84.19  | 86.90     | 88.90     | 89.40     | 89.32     | 89.48     |
+| CogView4-6B     |    85.13  | 83.85     | 90.35     | 91.17     | 91.14     | 87.29     |
+| **HiDream-I1**  |  **85.89**| 76.44 	  | 90.22     | 89.48     | 93.74     | 91.83     | 
+
+### GenEval
+
+| Model           | Overall  | Single Obj. | Two Obj. | Counting | Colors   | Position | Color attribution |
+|-----------------|----------|-------------|----------|----------|----------|----------|-------------------|
+| SDXL            |    0.55  | 0.98        | 0.74     | 0.39     | 0.85     | 0.15     | 0.23              |
+| PixArt-alpha    |    0.48  | 0.98        | 0.50     | 0.44     | 0.80     | 0.08     | 0.07              |
+| Flux.1-dev      |    0.66  | 0.98        | 0.79     | 0.73     | 0.77     | 0.22     | 0.45              |
+| DALL-E 3        |    0.67  | 0.96        | 0.87     | 0.47     | 0.83     | 0.43     | 0.45              |
+| CogView4-6B     |    0.73  | 0.99        | 0.86     | 0.66     | 0.79     | 0.48     | 0.58              |
+| SD3-Medium      |    0.74  | 0.99        | 0.94     | 0.72     | 0.89     | 0.33     | 0.60              |
+| Janus-Pro-7B    |    0.80  | 0.99        | 0.89     | 0.59     | 0.90     | 0.79     | 0.66              |
+| **HiDream-I1**  |  **0.83**| 1.00        | 0.98 	  | 0.79 	 | 0.91 	| 0.60 	   | 0.72              |
+
+### HPSv2.1 benchmark
+
+|  Model                  |     Averaged   | Animation  |  Concept-art  |   Painting   |   Photo    |
+|-------------------------|----------------|------------|---------------|--------------|------------|
+|  Stable Diffusion v2.0  |       26.38    |	27.09   |      26.02    |    25.68     |    26.73   |
+|  Midjourney V6          |       30.29    |    32.02   |      30.29    |    29.74     |    29.10   |
+|  SDXL	                  |       30.64    |    32.84   |      31.36    |    30.86     |    27.48   |
+|  Dall-E3	              |       31.44    |    32.39   |      31.09    |    31.18     |    31.09   |
+|  SD3                    |       31.53    |    32.60   |      31.82    |    32.06     |    29.62   |
+|  Midjourney V5          |       32.33    |    34.05   |      32.47    |    32.24     |    30.56   |
+|  CogView4-6B            |       32.31    |    33.23   |      32.60    |    32.89     |    30.52   |
+|  Flux.1-dev             |       32.47    |    33.87   |      32.27    |    32.62     |    31.11   |
+|  stable cascade         |       32.95    |    34.58   |      33.13    |    33.29     |    30.78   |
+|  **HiDream-I1**         |     **33.82**  |    35.05   |      33.74    |    33.88     |    32.61   |
+
+
+## License Agreement
+The Transformer models in this repository are licensed under the MIT License. The VAE is from `FLUX.1 [schnell]`, and the text encoders from `google/t5-v1_1-xxl` and `meta-llama/Meta-Llama-3.1-8B-Instruct`. Please follow the license terms specified for these components. You own all content you create with this model. You can use your generated content freely, but you must comply with this license agreement. You are responsible for how you use the models. Do not create illegal content, harmful material, personal information that could harm others, false information, or content targeting vulnerable groups.
+
+
+## Acknowledgements
+- The VAE component is from `FLUX.1 [schnell]`, licensed under Apache 2.0. 
+- The text encoders are from `google/t5-v1_1-xxl` (licensed under Apache 2.0) and `meta-llama/Meta-Llama-3.1-8B-Instruct` (licensed under the Llama 3.1 Community License Agreement).

model_index.json

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+  ],
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+    "CLIPTextModelWithProjection"
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+    "PreTrainedTokenizerFast"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

scheduler/scheduler_config.json

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+  "_diffusers_version": "0.29.0.dev0",
+  "num_train_timesteps": 1000,
+  "shift": 3.0
+}

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tokenizer/special_tokens_map.json

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tokenizer/tokenizer_config.json

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tokenizer_2/special_tokens_map.json

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tokenizer_3/special_tokens_map.json

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+    "<extra_id_83>",
+    "<extra_id_84>",
+    "<extra_id_85>",
+    "<extra_id_86>",
+    "<extra_id_87>",
+    "<extra_id_88>",
+    "<extra_id_89>",
+    "<extra_id_90>",
+    "<extra_id_91>",
+    "<extra_id_92>",
+    "<extra_id_93>",
+    "<extra_id_94>",
+    "<extra_id_95>",
+    "<extra_id_96>",
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+    "<extra_id_98>",
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+  "legacy": true,
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "T5Tokenizer",
+  "unk_token": "<unk>"
+}

tokenizer_4/special_tokens_map.json

@@ -0,0 +1,16 @@
+{
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_4/tokenizer_config.json

@@ -0,0 +1,2062 @@
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+  },
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n    {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n            {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n            {%- for arg_name, arg_val in tool_call.arguments | items %}\n                {{- arg_name + '=\"' + arg_val + '\"' }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n                {%- endfor %}\n            {{- \")\" }}\n        {%- else  %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n            {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n            {{- '\"parameters\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- \"}\" }}\n        {%- endif %}\n        {%- if builtin_tools is defined %}\n            {#- This means we're in ipython mode #}\n            {{- \"<|eom_id|>\" }}\n        {%- else %}\n            {{- \"<|eot_id|>\" }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}

transformer/config.json

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+{
+  "_class_name": "HiImageTransformer2DModel",
+  "_diffusers_version": "0.32.1",
+  "attention_head_dim": 128,
+  "axes_dims_rope": [
+    64,
+    32,
+    32
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+  "caption_channels": [
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+  "max_resolution": [
+    128,
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+  "llama_layers": [
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+  "num_attention_heads": 20,
+  "num_routed_experts": 4,
+  "num_activated_experts": 2,
+  "num_layers": 16,
+  "num_single_layers": 32,
+  "out_channels": 16,
+  "patch_size": 2,
+  "text_emb_dim": 2048
+}

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+  "_class_name": "AutoencoderKL",
+  "_diffusers_version": "0.30.0.dev0",
+  "_name_or_path": "../checkpoints/flux-dev",
+  "act_fn": "silu",
+  "block_out_channels": [
+    128,
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+  ],
+  "down_block_types": [
+    "DownEncoderBlock2D",
+    "DownEncoderBlock2D",
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+  "force_upcast": true,
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