[new-model] Add native Helios-Distilled T2V pipeline (#1670)

Co-authored-by: SolitaryThinker <wlsaidhi@gmail.com> Co-authored-by: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
2026-10-07 03:18:24 -07:00
parent a0291a57c1
commit 37b9dc1836
33 changed files with 4858 additions and 7 deletions
@@ -0,0 +1,85 @@
+# SPDX-License-Identifier: Apache-2.0
+"""Generate one Helios-Distilled T2V chunk through FastVideo's typed API.
+
+Set ``HELIOS_MODEL_PATH`` to a local snapshot to avoid downloading the public
+checkpoint again. The 33-frame example is a short integration run; increase
+``num_frames`` to 240 for the official eight-chunk default.
+"""
+
+from __future__ import annotations
+
+import os
+
+from fastvideo import VideoGenerator
+from fastvideo.api import (
+    EngineConfig,
+    GenerationRequest,
+    GeneratorConfig,
+    OffloadConfig,
+    OutputConfig,
+    SamplingConfig,
+)
+
+MODEL_PATH = os.getenv("HELIOS_MODEL_PATH", "BestWishYsh/Helios-Distilled")
+OUTPUT_PATH = os.getenv(
+    "HELIOS_OUTPUT_PATH",
+    "outputs_video/helios/helios_distilled_t2v.mp4",
+)
+PROMPT = ("A vibrant tropical fish swims gracefully through a colorful coral reef "
+          "in clear turquoise water, cinematic close-up, fluid motion, vivid detail.")
+NEGATIVE_PROMPT = ("Bright tones, overexposed, static, blurred details, subtitles, paintings, "
+                   "images, overall gray, worst quality, low quality, JPEG artifacts, ugly, "
+                   "deformed, disfigured, still picture, messy background.")
+
+
+def main() -> None:
+    generator = VideoGenerator.from_config(
+        GeneratorConfig(
+            model_path=MODEL_PATH,
+            engine=EngineConfig(
+                num_gpus=1,
+                use_fsdp_inference=False,
+                offload=OffloadConfig(
+                    dit=False,
+                    dit_layerwise=True,
+                    text_encoder=True,
+                    vae=True,
+                    pin_cpu_memory=False,
+                ),
+            ),
+        ))
+    request = GenerationRequest(
+        prompt=PROMPT,
+        negative_prompt=NEGATIVE_PROMPT,
+        sampling=SamplingConfig(
+            seed=42,
+            height=384,
+            width=640,
+            num_frames=33,
+            fps=24,
+            num_inference_steps=2,
+            guidance_scale=1.0,
+            pyramid_num_inference_steps_list=[2, 2, 2],
+            history_sizes=[16, 2, 1],
+            num_latent_frames_per_chunk=9,
+            keep_first_frame=True,
+            is_skip_first_chunk=False,
+            use_zero_init=True,
+            zero_steps=1,
+            is_amplify_first_chunk=True,
+        ),
+        output=OutputConfig(
+            output_path=OUTPUT_PATH,
+            save_video=True,
+            return_frames=False,
+        ),
+    )
+
+    try:
+        generator.generate(request=request)
+    finally:
+        generator.shutdown()
+
+
+if __name__ == "__main__":
+    main()