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README.md

@@ -1,14 +1,60 @@
 ---
-title: Vid Create
-emoji: 😻
-colorFrom: indigo
-colorTo: red
+title: LTX Video Generator
+emoji: 🎬
+colorFrom: purple
+colorTo: pink
 sdk: gradio
-sdk_version: 6.20.0
-python_version: '3.12'
+sdk_version: 5.0.1
 app_file: app.py
 pinned: false
-short_description: Create vids
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# LTX Video Generator (Personal Use)
+
+A free text-to-video generator built on [LTX-Video](https://huggingface.co/Lightricks/LTX-Video),
+running as a Hugging Face Space with a Gradio UI.
+
+## Deploy steps
+
+1. Go to https://huggingface.co/new-space
+2. Fill in:
+   - **Space name**: e.g. `my-ltx-video-generator`
+   - **SDK**: Gradio
+   - **Hardware**:
+     - Free CPU works but will be very slow (many minutes per clip).
+     - **ZeroGPU** is free if your account is eligible — best option for personal use.
+     - Or pick a paid GPU tier (e.g. T4/A10G) billed by the minute if you want faster, always-on generation.
+   - **Visibility**: Private (recommended, since this is personal use) or Public.
+3. Once the Space is created, upload these three files (or push via git — see below):
+   - `app.py`
+   - `requirements.txt`
+   - `README.md`
+4. The Space will build automatically. First build takes a while — it has to
+   download the LTX-Video model weights (several GB).
+5. Once it says "Running", open the app and generate your first clip.
+
+## Uploading via git (alternative to the web UI)
+
+```bash
+git clone https://huggingface.co/spaces/YOUR_USERNAME/my-ltx-video-generator
+cd my-ltx-video-generator
+# copy in app.py, requirements.txt, README.md
+git add .
+git commit -m "Initial LTX video generator"
+git push
+```
+
+You'll need a Hugging Face **access token** (with "write" scope) to push:
+Settings → Access Tokens → New token, then use it as your password when git
+prompts for credentials (username = your HF username).
+
+## Notes
+
+- LTX-Video is gated/openly licensed under its own model license — the first
+  time the Space downloads it, you may need to have accepted the license on
+  the [model page](https://huggingface.co/Lightricks/LTX-Video) with the same
+  account that owns the Space.
+- Generation settings (resolution, frame count, steps) are exposed in the UI
+  so you can trade off speed vs. quality.
+- This is set up for personal/private use — keep the Space private if you
+  don't want to share generations publicly.

app.py

@@ -0,0 +1,95 @@
+import spaces
+import torch
+import gradio as gr
+from diffusers import LTXPipeline
+from diffusers.utils import export_to_video
+
+MODEL_ID = "Lightricks/LTX-Video"
+
+# Load once at startup. On a GPU Space this lands on CUDA; on a ZeroGPU
+# Space, the @spaces.GPU decorator below handles moving things to GPU
+# only while a request is running.
+pipe = LTXPipeline.from_pretrained(MODEL_ID, torch_dtype=torch.bfloat16)
+pipe.to("cuda") if torch.cuda.is_available() else None
+
+DEFAULT_NEGATIVE = (
+    "worst quality, inconsistent motion, blurry, jittery, distorted, "
+    "low resolution, deformed"
+)
+
+
+@spaces.GPU(duration=120)  # ignored/no-op on non-ZeroGPU hardware
+def generate(prompt, negative_prompt, width, height, num_frames, steps, guidance, seed):
+    if not prompt or not prompt.strip():
+        raise gr.Error("Please enter a prompt describing the video you want.")
+
+    generator = None
+    if seed is not None and int(seed) >= 0:
+        generator = torch.Generator(device="cuda" if torch.cuda.is_available() else "cpu")
+        generator.manual_seed(int(seed))
+
+    video = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt or DEFAULT_NEGATIVE,
+        width=int(width),
+        height=int(height),
+        num_frames=int(num_frames),
+        num_inference_steps=int(steps),
+        guidance_scale=float(guidance),
+        generator=generator,
+    ).frames[0]
+
+    out_path = "/tmp/output.mp4"
+    export_to_video(video, out_path, fps=24)
+    return out_path
+
+
+with gr.Blocks(title="Free LTX Video Generator") as demo:
+    gr.Markdown(
+        """
+        # 🎬 LTX Video Generator
+        Personal text-to-video generator powered by [LTX-Video](https://huggingface.co/Lightricks/LTX-Video).
+        Describe a scene and generate a short clip.
+        """
+    )
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            prompt = gr.Textbox(
+                label="Prompt",
+                placeholder="A golden retriever running through a field of sunflowers at sunset, cinematic lighting",
+                lines=4,
+            )
+            negative_prompt = gr.Textbox(
+                label="Negative prompt (optional)",
+                value=DEFAULT_NEGATIVE,
+                lines=2,
+            )
+            with gr.Row():
+                width = gr.Slider(256, 1280, value=704, step=32, label="Width")
+                height = gr.Slider(256, 1280, value=480, step=32, label="Height")
+            with gr.Row():
+                num_frames = gr.Slider(9, 161, value=65, step=8, label="Number of frames")
+                steps = gr.Slider(10, 50, value=30, step=1, label="Inference steps")
+            with gr.Row():
+                guidance = gr.Slider(1.0, 10.0, value=3.0, step=0.1, label="Guidance scale")
+                seed = gr.Number(value=-1, label="Seed (-1 = random)")
+            run_btn = gr.Button("Generate Video", variant="primary")
+
+        with gr.Column(scale=1):
+            output_video = gr.Video(label="Result")
+
+    run_btn.click(
+        fn=generate,
+        inputs=[prompt, negative_prompt, width, height, num_frames, steps, guidance, seed],
+        outputs=output_video,
+    )
+
+    gr.Markdown(
+        "Tip: keep width/height multiples of 32 and frames as `8n+1` "
+        "(e.g. 65, 97, 121) — these match LTX-Video's training constraints "
+        "and avoid shape errors."
+    )
+
+if __name__ == "__main__":
+    demo.queue(max_size=10).launch()

requirements.txt

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+git+https://github.com/huggingface/diffusers.git
+transformers>=4.44.0
+accelerate>=0.33.0
+sentencepiece
+imageio
+imageio-ffmpeg
+torch
+spaces
+gradio