Duplicate from huggingface-tools/text-to-video

Co-authored-by: Lysandre <[email protected]>

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README.md

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+---
+title: Text to Video
+emoji: ⚡
+colorFrom: red
+colorTo: green
+sdk: gradio
+sdk_version: 3.27.0
+app_file: app.py
+pinned: false
+tags:
+- tool
+duplicated_from: huggingface-tools/text-to-video
+---

app.py

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+from transformers.tools.base import launch_gradio_demo
+from text_to_video import TextToVideoTool
+
+launch_gradio_demo(TextToVideoTool)

requirements.txt

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+transformers @ git+https://github.com/huggingface/transformers@test_composition
+diffusers
+accelerate
+torch

text_to_video.py

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+import torch
+
+from transformers.tools.base import Tool, get_default_device
+from transformers.utils import is_accelerate_available
+
+from diffusers import DiffusionPipeline
+
+
+TEXT_TO_VIDEO_DESCRIPTION = (
+    "This is a tool that creates a video according to a text description. It takes an input named `prompt` which "
+    "contains the image description, as well as an optional input `seconds` which will be the duration of the video. "
+    "The default is of two seconds. The tool outputs a video object."
+)
+
+
+class TextToVideoTool(Tool):
+    default_checkpoint = "damo-vilab/text-to-video-ms-1.7b"
+    description = TEXT_TO_VIDEO_DESCRIPTION
+    inputs = ['text']
+    outputs = ['video']
+
+    def __init__(self, device=None, **hub_kwargs) -> None:
+        if not is_accelerate_available():
+            raise ImportError("Accelerate should be installed in order to use tools.")
+
+        super().__init__()
+
+        self.device = device
+        self.pipeline = None
+        self.hub_kwargs = hub_kwargs
+
+    def setup(self):
+        if self.device is None:
+            self.device = get_default_device()
+
+        self.pipeline = DiffusionPipeline.from_pretrained(
+            self.default_checkpoint, variant="fp16"
+        )
+        self.pipeline.to(self.device)
+
+        self.is_initialized = True
+
+    def __call__(self, prompt, seconds=2):
+        if not self.is_initialized:
+            self.setup()
+
+        return self.pipeline(prompt, num_frames=8 * seconds).frames
+

tool_config.json

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+{
+  "description": "This is a tool that creates a video according to a text description. It takes an input named `prompt` which contains the image description, as well as an optional input `seconds` which will be the duration of the video. The default is of two seconds. The tool outputs a video object.",
+  "name": "video_generator",
+  "tool_class": "text_to_video.TextToVideoTool"
+}