vllm-omni/examples/offline_inference/x_to_text

X-To-Text

Generate text from text or image inputs with vLLM-Omni's shared offline entrypoint.

• x_to_text.py: command-line script for text-to-text (T2T) and image-to-text (I2T) inference.

Supported Models

Model	T2T	I2T	Default deploy config
ByteDance-Seed/BAGEL-7B-MoT	Yes	Yes	vllm_omni/deploy/bagel.yaml
tencent/HunyuanImage-3.0-Instruct	Yes	Yes	vllm_omni/deploy/hunyuan_image3_ar.yaml
bytedance-research/MammothModa2-Preview	Yes	Yes	vllm_omni/deploy/mammoth_moda2_ar.yaml
bytedance-research/MammothModa2-Dev	Yes	Yes	vllm_omni/deploy/mammoth_moda2_ar.yaml

The script recognizes these model families from config.json, applies the model-specific prompt format, and selects an AR-only deploy for HunyuanImage-3 and MammothModa2. BAGEL uses its registered default deploy.

Text-To-Text

BAGEL

python examples/offline_inference/x_to_text/x_to_text.py \
  --model ByteDance-Seed/BAGEL-7B-MoT \
  --prompt "Where is the capital of France?"

HunyuanImage-3

python examples/offline_inference/x_to_text/x_to_text.py \
  --model tencent/HunyuanImage-3.0-Instruct \
  --prompt "Explain multimodal inference in three concise sentences."

MammothModa2

python examples/offline_inference/x_to_text/x_to_text.py \
  --model bytedance-research/MammothModa2-Preview \
  --prompt "Explain multimodal inference in three concise sentences."

The same command supports the Dev checkpoint:

python examples/offline_inference/x_to_text/x_to_text.py \
  --model bytedance-research/MammothModa2-Dev \
  --prompt "Explain multimodal inference in three concise sentences."

Image-To-Text

Pass one image with --image. The default question can be replaced with any instruction supported by the checkpoint.

python examples/offline_inference/x_to_text/x_to_text.py \
  --model ByteDance-Seed/BAGEL-7B-MoT \
  --image image.png \
  --prompt "Describe this image in detail."

Use the same command with either of the other supported checkpoints:

python examples/offline_inference/x_to_text/x_to_text.py \
  --model tencent/HunyuanImage-3.0-Instruct \
  --image image.png \
  --prompt "Describe this image in detail."

python examples/offline_inference/x_to_text/x_to_text.py \
  --model bytedance-research/MammothModa2-Preview \
  --image image.png \
  --prompt "Describe this image in detail."

Use bytedance-research/MammothModa2-Dev in the same command to run I2T with the Dev checkpoint.

Key Arguments

Argument	Default	Description
--model	Required	Hugging Face model ID or local checkpoint path
--prompt	Required	User question or instruction
--image	None	Input image; enables I2T when supplied
--output	None	Optional text output file
--deploy-config	Model default	Override the deploy YAML
--max-tokens	512	Maximum generated tokens
--temperature	0.0	Sampling temperature
--top-p	1.0	Nucleus sampling probability
--seed	42	Sampling seed
--trust-remote-code	Off	Allow checkpoint-provided Python code
--enforce-eager	Off	Disable graph compilation

Hardware Notes

The committed HunyuanImage-3 AR-only default uses four GPUs with TP=4. To use a different topology, pass a custom AR-only YAML through --deploy-config. BAGEL and MammothModa2 use their repository deploy defaults unless overridden.