3.5 KiB
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.