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Generate videos from prompts using LTX Video-0.9.7 13B Distilled and custom LoRA
Example
Details
- Accepts
- text
Pricing
- Price
- 5 cr / video
Prices in credits (1 credit = $0.01).
Data schema
Input
| Field | Type | Description |
|---|---|---|
| seed | — | Random seed for generation |
| loras | array | LoRA weights to use for generation |
| promptrequired | string | Text prompt to guide generation |
| frame_rate | integer | The frame rate of the video. |
| num_frames | integer | The number of frames in the video. |
| resolution | stringenum: 480p, 720p | Resolution of the generated video. |
| aspect_ratio | stringenum: 9:16, 1:1, 16:9 | Aspect ratio of the generated video. |
| expand_prompt | boolean | Whether to expand the prompt using a language model. |
| reverse_video | boolean | Whether to reverse the video. |
| negative_prompt | string | Negative prompt for generation |
| enable_detail_pass | boolean | Whether to use a detail pass. If True, the model will perform a second pass to refine the video and enhance details. This incurs a 2.0x cost multiplier on the base price. |
| enable_safety_checker | boolean | Whether to enable the safety checker. Disabling it requires account authorization; unauthorized requests are always checked. |
| temporal_adain_factor | number | The factor for adaptive instance normalization (AdaIN) applied to generated video chunks after the first. This can help deal with a gradual increase in saturation/contrast in the generated video by normalizing the color distribution across the video. A high value will ensure the color distribution i… |
| tone_map_compression_ratio | number | The compression ratio for tone mapping. This is used to compress the dynamic range of the video to improve visual quality. A value of 0.0 means no compression, while a value of 1.0 means maximum compression. |
| first_pass_num_inference_steps | integer | Number of inference steps during the first pass. |
| second_pass_skip_initial_steps | integer | The number of inference steps to skip in the initial steps of the second pass. By skipping some steps at the beginning, the second pass can focus on smaller details instead of larger changes. |
| second_pass_num_inference_steps | integer | Number of inference steps during the second pass. |
Output
| Field | Type | Description |
|---|---|---|
| seed | integer | The seed used for generation. |
| video | — | The generated video file. |
| prompt | string | The prompt used for generation. |