a-r-r-o-w HF staff commited on
Commit
b8003d6
1 Parent(s): c9d1e5b

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +85 -193
README.md CHANGED
@@ -1,198 +1,90 @@
1
  ---
2
  library_name: diffusers
 
 
 
3
  ---
4
 
5
- # Model Card for Model ID
6
 
7
- <!-- Provide a quick summary of what the model is/does. -->
8
-
9
-
10
-
11
- ## Model Details
12
-
13
- ### Model Description
14
-
15
- <!-- Provide a longer summary of what this model is. -->
16
-
17
- This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
18
-
19
- - **Developed by:** [More Information Needed]
20
- - **Funded by [optional]:** [More Information Needed]
21
- - **Shared by [optional]:** [More Information Needed]
22
- - **Model type:** [More Information Needed]
23
- - **Language(s) (NLP):** [More Information Needed]
24
- - **License:** [More Information Needed]
25
- - **Finetuned from model [optional]:** [More Information Needed]
26
-
27
- ### Model Sources [optional]
28
-
29
- <!-- Provide the basic links for the model. -->
30
-
31
- - **Repository:** [More Information Needed]
32
- - **Paper [optional]:** [More Information Needed]
33
- - **Demo [optional]:** [More Information Needed]
34
-
35
- ## Uses
36
-
37
- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
38
-
39
- ### Direct Use
40
-
41
- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
42
-
43
- [More Information Needed]
44
-
45
- ### Downstream Use [optional]
46
-
47
- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
48
-
49
- [More Information Needed]
50
-
51
- ### Out-of-Scope Use
52
-
53
- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
54
-
55
- [More Information Needed]
56
-
57
- ## Bias, Risks, and Limitations
58
-
59
- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
60
-
61
- [More Information Needed]
62
-
63
- ### Recommendations
64
-
65
- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
66
-
67
- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
68
-
69
- ## How to Get Started with the Model
70
-
71
- Use the code below to get started with the model.
72
-
73
- [More Information Needed]
74
-
75
- ## Training Details
76
-
77
- ### Training Data
78
-
79
- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
80
-
81
- [More Information Needed]
82
-
83
- ### Training Procedure
84
-
85
- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
86
-
87
- #### Preprocessing [optional]
88
-
89
- [More Information Needed]
90
-
91
-
92
- #### Training Hyperparameters
93
-
94
- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
95
-
96
- #### Speeds, Sizes, Times [optional]
97
-
98
- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
99
-
100
- [More Information Needed]
101
-
102
- ## Evaluation
103
-
104
- <!-- This section describes the evaluation protocols and provides the results. -->
105
-
106
- ### Testing Data, Factors & Metrics
107
-
108
- #### Testing Data
109
-
110
- <!-- This should link to a Dataset Card if possible. -->
111
-
112
- [More Information Needed]
113
-
114
- #### Factors
115
-
116
- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
117
-
118
- [More Information Needed]
119
-
120
- #### Metrics
121
-
122
- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
123
-
124
- [More Information Needed]
125
-
126
- ### Results
127
-
128
- [More Information Needed]
129
-
130
- #### Summary
131
-
132
-
133
-
134
- ## Model Examination [optional]
135
-
136
- <!-- Relevant interpretability work for the model goes here -->
137
-
138
- [More Information Needed]
139
-
140
- ## Environmental Impact
141
-
142
- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
143
-
144
- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
145
-
146
- - **Hardware Type:** [More Information Needed]
147
- - **Hours used:** [More Information Needed]
148
- - **Cloud Provider:** [More Information Needed]
149
- - **Compute Region:** [More Information Needed]
150
- - **Carbon Emitted:** [More Information Needed]
151
-
152
- ## Technical Specifications [optional]
153
-
154
- ### Model Architecture and Objective
155
-
156
- [More Information Needed]
157
-
158
- ### Compute Infrastructure
159
-
160
- [More Information Needed]
161
-
162
- #### Hardware
163
-
164
- [More Information Needed]
165
-
166
- #### Software
167
-
168
- [More Information Needed]
169
-
170
- ## Citation [optional]
171
-
172
- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
173
-
174
- **BibTeX:**
175
-
176
- [More Information Needed]
177
-
178
- **APA:**
179
-
180
- [More Information Needed]
181
-
182
- ## Glossary [optional]
183
-
184
- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
185
-
186
- [More Information Needed]
187
-
188
- ## More Information [optional]
189
-
190
- [More Information Needed]
191
-
192
- ## Model Card Authors [optional]
193
-
194
- [More Information Needed]
195
-
196
- ## Model Card Contact
197
-
198
- [More Information Needed]
 
1
  ---
2
  library_name: diffusers
3
+ pipeline_tag: text-to-video
4
+ tags:
5
+ - animatediff
6
  ---
7
 
 
8
 
9
+ AnimateDiff is a method that allows you to create videos using pre-existing Stable Diffusion Text to Image models.
10
+
11
+ It achieves this by inserting motion module layers into a frozen text to image model and training it on video clips to extract a motion prior.
12
+ These motion modules are applied after the ResNet and Attention blocks in the Stable Diffusion UNet. Their purpose is to introduce coherent motion across image frames. To support these modules we introduce the concepts of a MotionAdapter and UNetMotionModel. These serve as a convenient way to use these motion modules with existing Stable Diffusion models.
13
+
14
+ SparseControlNetModel is an implementation of ControlNet for [AnimateDiff](https://arxiv.org/abs/2307.04725).
15
+
16
+ ControlNet was introduced in [Adding Conditional Control to Text-to-Image Diffusion Models](https://huggingface.co/papers/2302.05543) by Lvmin Zhang, Anyi Rao, and Maneesh Agrawala.
17
+
18
+ The SparseCtrl version of ControlNet was introduced in [SparseCtrl: Adding Sparse Controls to Text-to-Video Diffusion Models](https://arxiv.org/abs/2311.16933) for achieving controlled generation in text-to-video diffusion models by Yuwei Guo, Ceyuan Yang, Anyi Rao, Maneesh Agrawala, Dahua Lin, and Bo Dai.
19
+
20
+ The following example demonstrates how you can utilize the motion modules and sparse controlnet with an existing Stable Diffusion text to image model.
21
+
22
+ <table align="center">
23
+ <tr>
24
+ <center>
25
+ <b>closeup face photo of man in black clothes, night city street, bokeh, fireworks in background</b>
26
+ </center>
27
+ </tr>
28
+ <tr>
29
+ <td>
30
+ <center>
31
+ <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatediff-firework.png" alt="closeup face photo of man in black clothes, night city street, bokeh, fireworks in background" />
32
+ </center>
33
+ </td>
34
+ <td>
35
+ <center>
36
+ <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatediff-sparsectrl-rgb-result.gif" alt="closeup face photo of man in black clothes, night city street, bokeh, fireworks in background" />
37
+ </center>
38
+ </td>
39
+ </tr>
40
+ </table>
41
+
42
+ ```python
43
+ import torch
44
+
45
+ from diffusers import AnimateDiffSparseControlNetPipeline
46
+ from diffusers.models import AutoencoderKL, MotionAdapter, SparseControlNetModel
47
+ from diffusers.schedulers import DPMSolverMultistepScheduler
48
+ from diffusers.utils import export_to_gif, load_image
49
+
50
+
51
+ model_id = "SG161222/Realistic_Vision_V5.1_noVAE"
52
+ motion_adapter_id = "guoyww/animatediff-motion-adapter-v1-5-3"
53
+ controlnet_id = "guoyww/animatediff-sparsectrl-rgb"
54
+ lora_adapter_id = "guoyww/animatediff-motion-lora-v1-5-3"
55
+ vae_id = "stabilityai/sd-vae-ft-mse"
56
+ device = "cuda"
57
+
58
+ motion_adapter = MotionAdapter.from_pretrained(motion_adapter_id, torch_dtype=torch.float16).to(device)
59
+ controlnet = SparseControlNetModel.from_pretrained(controlnet_id, torch_dtype=torch.float16).to(device)
60
+ vae = AutoencoderKL.from_pretrained(vae_id, torch_dtype=torch.float16).to(device)
61
+ scheduler = DPMSolverMultistepScheduler.from_pretrained(
62
+ model_id,
63
+ subfolder="scheduler",
64
+ beta_schedule="linear",
65
+ algorithm_type="dpmsolver++",
66
+ use_karras_sigmas=True,
67
+ )
68
+ pipe = AnimateDiffSparseControlNetPipeline.from_pretrained(
69
+ model_id,
70
+ motion_adapter=motion_adapter,
71
+ controlnet=controlnet,
72
+ vae=vae,
73
+ scheduler=scheduler,
74
+ torch_dtype=torch.float16,
75
+ ).to(device)
76
+ pipe.load_lora_weights(lora_adapter_id, adapter_name="motion_lora")
77
+
78
+ image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatediff-firework.png")
79
+
80
+ video = pipe(
81
+ prompt="closeup face photo of man in black clothes, night city street, bokeh, fireworks in background",
82
+ negative_prompt="low quality, worst quality",
83
+ num_inference_steps=25,
84
+ conditioning_frames=image,
85
+ controlnet_frame_indices=[0],
86
+ controlnet_conditioning_scale=1.0,
87
+ generator=torch.Generator().manual_seed(42),
88
+ ).frames[0]
89
+ export_to_gif(video, "output.gif")
90
+ ```