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temporary readme

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  1. README.md +1 -81
  2. README_WIP.md +97 -0
README.md CHANGED
@@ -13,84 +13,4 @@ short_description: All-in-one tool for AI video training
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  # 🎥 Video Model Studio (VMS)
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- ## Presentation
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-
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- VMS is an all-in-one tool to train LoRA models for various open-source AI video models:
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-
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- - Data collection from various sources
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- - Splitting videos into short single camera shots
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- - Automatic captioning
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- - Training HunyuanVideo or LTX-Video
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-
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- ## Similar projects
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-
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- I wasn't aware of it when I started this project,
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- but there is also this: https://github.com/alisson-anjos/diffusion-pipe-ui
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-
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- ## Installation
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-
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- VMS is built on top of Finetrainers and Gradio, and designed to run as a Hugging Face Space (but you can deploy it elsewhere if you want to).
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-
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- ### Full installation at Hugging Face
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-
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- Easy peasy: create a Space (make sure to use the `Gradio` type/template), and push the repo. No Docker needed!
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-
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- ### Dev mode on Hugging Face
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-
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- Enable dev mode in the space, then open VSCode in local or remote and run:
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-
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- ```
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- pip install -r requirements.txt
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- ```
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-
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- As this is not automatic, then click on "Restart" in the space dev mode UI widget.
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-
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- ### Full installation somewhere else
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-
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- I haven't tested it, but you can try to provided Dockerfile
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-
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- ### Full installation in local
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-
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- the full installation requires:
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- - Linux
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- - CUDA 12
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- - Python 3.10
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-
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- This is because of flash attention, which is defined in the `requirements.txt` using an URL to download a prebuilt wheel (python bindings for a native library)
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-
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- ```bash
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- ./setup.sh
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- ```
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-
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- ### Degraded installation in local
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-
67
- If you cannot meet the requirements, you can:
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-
69
- - solution 1: fix requirements.txt to use another prebuilt wheel
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- - solution 2: manually build/install flash attention
71
- - solution 3: don't use clip captioning
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-
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- Here is how to do solution 3:
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- ```bash
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- ./setup_no_captions.sh
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- ```
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-
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- ## Run
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-
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- ### Running the Gradio app
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-
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- Note: please make sure you properly define the environment variables for `STORAGE_PATH` (eg. `/data/`) and `HF_HOME` (eg. `/data/huggingface/`)
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-
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- ```bash
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- python app.py
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- ```
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-
88
- ### Running locally
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-
90
- See above remarks about the environment variable.
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-
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- By default `run.sh` will store stuff in `.data/` (located inside the current working directory):
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-
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- ```bash
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- ./run.sh
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- ```
 
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  # 🎥 Video Model Studio (VMS)
15
 
16
+ This project is a work in progress, not all features are working yet (there are some issue with the automatic captioning).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
README_WIP.md ADDED
@@ -0,0 +1,97 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ README_WIP.md
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+ ---
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+ title: Video Model Studio
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+ emoji: 🎥
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+ colorFrom: gray
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+ colorTo: gray
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+ sdk: gradio
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+ sdk_version: 5.15.0
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+ app_file: app.py
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+ pinned: true
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+ license: apache-2.0
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+ short_description: All-in-one tool for AI video training
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+ ---
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+
15
+ # 🎥 Video Model Studio (VMS)
16
+
17
+ ## Presentation
18
+
19
+ VMS is an all-in-one tool to train LoRA models for various open-source AI video models:
20
+
21
+ - Data collection from various sources
22
+ - Splitting videos into short single camera shots
23
+ - Automatic captioning
24
+ - Training HunyuanVideo or LTX-Video
25
+
26
+ ## Similar projects
27
+
28
+ I wasn't aware of it when I started this project,
29
+ but there is also this: https://github.com/alisson-anjos/diffusion-pipe-ui
30
+
31
+ ## Installation
32
+
33
+ VMS is built on top of Finetrainers and Gradio, and designed to run as a Hugging Face Space (but you can deploy it elsewhere if you want to).
34
+
35
+ ### Full installation at Hugging Face
36
+
37
+ Easy peasy: create a Space (make sure to use the `Gradio` type/template), and push the repo. No Docker needed!
38
+
39
+ ### Dev mode on Hugging Face
40
+
41
+ Enable dev mode in the space, then open VSCode in local or remote and run:
42
+
43
+ ```
44
+ pip install -r requirements.txt
45
+ ```
46
+
47
+ As this is not automatic, then click on "Restart" in the space dev mode UI widget.
48
+
49
+ ### Full installation somewhere else
50
+
51
+ I haven't tested it, but you can try to provided Dockerfile
52
+
53
+ ### Full installation in local
54
+
55
+ the full installation requires:
56
+ - Linux
57
+ - CUDA 12
58
+ - Python 3.10
59
+
60
+ This is because of flash attention, which is defined in the `requirements.txt` using an URL to download a prebuilt wheel (python bindings for a native library)
61
+
62
+ ```bash
63
+ ./setup.sh
64
+ ```
65
+
66
+ ### Degraded installation in local
67
+
68
+ If you cannot meet the requirements, you can:
69
+
70
+ - solution 1: fix requirements.txt to use another prebuilt wheel
71
+ - solution 2: manually build/install flash attention
72
+ - solution 3: don't use clip captioning
73
+
74
+ Here is how to do solution 3:
75
+ ```bash
76
+ ./setup_no_captions.sh
77
+ ```
78
+
79
+ ## Run
80
+
81
+ ### Running the Gradio app
82
+
83
+ Note: please make sure you properly define the environment variables for `STORAGE_PATH` (eg. `/data/`) and `HF_HOME` (eg. `/data/huggingface/`)
84
+
85
+ ```bash
86
+ python app.py
87
+ ```
88
+
89
+ ### Running locally
90
+
91
+ See above remarks about the environment variable.
92
+
93
+ By default `run.sh` will store stuff in `.data/` (located inside the current working directory):
94
+
95
+ ```bash
96
+ ./run.sh
97
+ ```