Ltx2.3 Chinese Drama Charlora
A character LoRA for LTX-Video 2.3 (22B) trained on a 78-episode corpus of Chinese historical drama footage. Specialises the base model for live-action, photoreal cinematic generation in Han dynasty / wuxia settings,...
Fonte do modelo
- Tipo
- LoRA
- Tamanho do arquivo
- 816 MB
- Modelo base
- Lightricks/LTX-Video
- Versão
- vlora_weights_step_03000
- Atualizado
- 16 de out. de 2026
- Downloads
- 134
- Fonte
- Hugging Face
Descrição da fonte
LTX-2.3 Chinese Drama Character LoRA
A character LoRA for LTX-Video 2.3 (22B) trained on a 78-episode corpus of Chinese historical drama footage. Specialises the base model for live-action, photoreal cinematic generation in Han dynasty / wuxia settings, with stable identity for the most-frequent on-screen characters.
Model details
| Field | Value |
|---|---|
| Base model | Lightricks/LTX-2.3-22B |
| Adapter type | Plain LoRA (PEFT-style) |
| Rank | 64 |
| Alpha | 64 |
| Target modules | to_k, to_q, to_v, to_out.0 |
| Training steps | 3000 |
| Optimizer | AdamW |
| Learning rate | 1e-4, linear schedule |
| Mixed precision | bf16 |
| Gradient checkpointing | enabled |
Training data
- Source: 78 episodes of a Chinese historical drama (Han dynasty setting), processed at extraction time into ~750 clean shots.
- Caption format: enriched inline-weave prompts produced by Qwen3-Omni VL, with character identity triggers (
char_0_person,char_1_person, ...) substituted at the start of each prompt, followed by camera/scene prose and a style anchor (live-action photorealistic, cinematic Chinese drama). - Captions are bilingual (English + Simplified Chinese). The deployed LoRA was trained on the Chinese variants.
Usage
The character triggers char_0_person, char_1_person, etc. correspond to the most-frequent identity clusters discovered by ArcFace + DBSCAN over the corpus. They must appear at the start of the prompt, comma-separated, terminated with a period.
Prompt format
char_0_person, char_1_person. Framed in a static eye level medium shot,
on a 35mm normal lens, with natural light. Set in a torch-lit Han dynasty
courtyard at dusk, the subjects face each other in tense silence.
Live-action photorealistic, cinematic Chinese drama.
Loading with diffusers
from diffusers import LTXPipeline
import torch
pipe = LTXPipeline.from_pretrained(
"Lightricks/LTX-2.3-22B",
torch_dtype=torch.bfloat16,
)
pipe.to("cuda")
# Load the LoRA
pipe.load_lora_weights(
"SyFeee/ltx2.3-chinese-drama-charlora",
weight_name="lora_weights_step_03000.safetensors",
adapter_name="cn_drama_char",
)
pipe.set_adapters(["cn_drama_char"], adapter_weights=[0.9])
video = pipe(
prompt=(
"char_0_person. Framed in a close-up on a 50mm normal lens, with shallow focus. "
"Set in a candlelit Han dynasty study, the subject sits writing on bamboo scrolls. "
"Live-action photorealistic, cinematic Chinese drama."
),
negative_prompt="no CGI, no animation, no illustration, no painterly style, no anime",
width=1280,
height=544,
num_frames=89,
guidance_scale=4.0,
num_inference_steps=20,
).frames[0]
Recommended LoRA strength
0.8— subtle stylistic touch, identity present but soft0.9— default, validated against training distribution1.0+— risks overfitting on facial features at the expense of camera/scene freedom
What this LoRA does well
- Live-action photoreal output in the Han dynasty visual register (palace interiors, courtyards, traditional costume).
- Stable character identity across cuts when the same trigger is used.
- Strong response to camera/lens prose conventions baked into the training captions (
dolly in,35mm normal lens,handheld).
What it does NOT do
- It cannot generate characters it never saw in training (no zero-shot identity transfer).
- It is not an audio model. For audio-conditioned generation see the matching AV LoRA in the same project.
- It does not include the IC-LoRA control adapters (pose / depth / canny). Those are shipped as separate repositories.
Triggers in the trained corpus
The trigger naming follows the fallback format char_{id}_person. Cluster frequencies in the training corpus:
| Trigger | Clips |
|---|---|
char_0_person | 442 |
char_0_person, char_1_person | 180 |
char_0_person, char_1_person, char_2_person | 53 |
| 4–10 character combinations | 49 |
| No characters detected (style-only) | 20 |
So the model has the strongest signal for single-character and two-character compositions.
Related models
SyFeee/ltx2.3-chinese-drama-iclora-pose— pose-controlled IC-LoRA on the same corpus.SyFeee/ltx2.3-chinese-drama-iclora-depth— depth-controlled IC-LoRA.SyFeee/ltx2.3-chinese-drama-iclora-canny— canny-edge-controlled IC-LoRA.
License
Apache 2.0. See LICENSE for terms.
Attribution: SyFe.
Fontes
1 fonte
Fontes
1 fonteVerificado 24 de ago.
Artefatos de modelo
1 artefato
Artefatos de modelo
1 artefatolora_weights_step_03000.safetensors
safetensors · 816 MB · SHA-256 4bce983b76d8…cec2 · Hugging Face
Download fileTrechos de fonte
2 trechos
Trechos de fonte
2 trechos--- license: apache-2.0 base_model: Lightricks/LTX-Video tags: - lora - text-to-video - ltx-video - ltx-2.3 - chinese-drama - character-lora - cinematic language: - zh - en library_name: diffusers pipeline_tag: text-to-video --- # LTX-2.3 Chinese Drama Character LoRA A character LoRA for **LTX-Video 2.3 (22B)** trained on a 78-episode corpus of Chinese historical drama footage. Specialises the base model for live-action, photoreal cinematic generation in Han dynasty / wuxia settings, with stable identity for the most-frequent on-screen characters. ## Model details | Field | Value | |---|---| | Base model | `Lightricks/LTX-2.3-22B` | | Adapter type | Plain LoRA (PEFT-style) | | Rank | 64 | | Alpha | 64 | | Target modules | `to_k`, `to_q`, `to_v`, `to_out.0` | | Training steps | 3000 | | Optimizer | AdamW | | Learning rate | 1e-4, linear schedule | | Mixed precision | bf16 | | Gradient checkpointing | enabled | ## Training data * **Source**: 78 episodes of a Chinese historical drama (Han dynasty setting), processed at extraction time into ~750 clean shots. * **Caption format**: enriched inline-weave prompts produced by Qwen3-Omni VL, with character identity triggers (`char_0_person`, `char_1_person`, ...) substituted at the start of each prompt, followed by camera/scene prose and a style anchor (`live-action photorealistic, cinematic Chinese drama`). * **Captions are bilingual** (English + Simplified Chinese). The deployed LoRA was trained on the Chinese variants. ## Usage The character triggers `char_0_person`, `char_1_person`, etc. correspond to the most-frequent identity clusters discovered by ArcFace + DBSCAN over the corpus. They must appear at the start of the prompt, comma-separated, terminated with a period. ### Prompt format ``` char_0_person, char_1_person. Framed in a static eye level medium shot, on a 35mm normal lens, with natural light. Set in a torch-lit Han dynasty courtyard at dusk, the subjects face each other in tense silence. Live-action photorealistic, cinematic Chinese drama. ``` ### Loading with `diffusers` ```python from diffusers import LTXPipeline import torch pipe = LTXPipeline.from_pretrained( "Lightricks/LTX-2.3-22B", torch_dtype=torch.bfloat16, ) pipe.to("cuda") # Load the LoRA pipe.load_lora_weights( "SyFeee/ltx2.3-chinese-drama-charlora", weight_name="lora_weights_step_03000.safetensors", adapter_n...
Source context: 134 downloads · 1 likes · Pipeline text-to-video · Library diffusers · Repo SyFeee/ltx2.3-chinese-drama-charlora
