Singapore8B parameters262K contextVision + text

Explore Qwen SEA-LION v4 8B VL

Use AI Singapore’s popular Qwen vision-language model for multilingual visual Q&A, document understanding, extraction, and regional image reasoning. Use the playground to give Qwen SEA-LION v4 8B VL a representative input and review its output. Adjust the available settings to shape the result for your task.

Model

aisingapore/Qwen-SEA-LION-v4-8B-VL

Input

Configure your request

Optional ImageTextToTextPipeline images. Supply uploads here or image URLs inside a chat-formatted text value.

ImageTextToTextPipeline text: a prompt or JSON chat-message array. The model also supports text-only requests.

Documentation

Qwen SEA-LION v4 8B VL field reference

Use this reference to understand how every field in the playground changes the request sent to aisingapore/Qwen-SEA-LION-v4-8B-VL.

images

Optional

Type: File array

Default: None

Provides the visual inputs the model should analyze. The text field should identify the requested task and, with multiple images, clearly distinguish which image each instruction refers to; larger or numerous images consume more processing and context.

text

Required

Type: Text

Explains how the model should use the supplied image or video, such as describing a scene, extracting text, comparing items, or answering a question. Refer to relevant regions or frames explicitly when a precise visual answer is needed.

return_full_text

Optional

Type: Boolean

Default: On

Controls whether each result contains the original prompt followed by the completion or only the newly generated portion. Disable it when you need a clean completion without repeating the submitted input.

return_tensors

Optional

Type: Boolean

Default: Off

Returns numeric generated token IDs as tensors rather than ordinary readable text. This is useful for downstream model processing or custom decoding, but most applications should leave it off.

clean_up_tokenization_spaces

Optional

Type: Boolean

Default: On

Applies the tokenizer’s cleanup rules after decoding, such as removing spaces that were introduced around punctuation. Disable it when exact spacing or a lossless view of token decoding is more important than polished text.

continue_final_message

Optional

Type: Boolean

Default: Off

Treats the last chat message as an unfinished response that the model should continue. Use it to prefill the beginning or structure of an assistant answer; leave it off for a normal new reply to the conversation.

skip_special_tokens

Optional

Type: Boolean

Default: On

Removes internal tokens such as beginning-of-sequence, end-of-sequence, padding, and chat-control markers from readable output. Keep it enabled for user-facing text; disable it only when inspecting the model’s exact token sequence.

stop_sequence

Optional

Type: Text

Default: None

Ends generation as soon as the decoded output contains this exact sequence. The match is literal, so capitalization and spacing matter; choose a distinctive delimiter to avoid stopping on normal prose by accident.

timeout

Optional

Type: Integer

Default: 30

Range: 1–Unbounded

Limits how long the pipeline waits while downloading an image or other remote media source. Increase it for large files or slow hosts, and lower it when the application should fail quickly instead of holding a request open.

Maximum output tokens

Optional

Type: Integer

Default: 1024

Range: 1–262144

Caps how many tokens the model can add after the input. The model may stop earlier naturally, but a limit that is too low can cut off an answer; input tokens are not counted in this value.

generate_kwargs

Optional

Type: JSON object

Default: {"do_sample":true,"temperature":0.7,"top_p":0.8,"top_k":20,"repetition_penalty":1.0}

Provides advanced keyword arguments directly to the model’s generation method. Use it for supported controls that are not shown separately in the form, and avoid duplicating named settings because these values may override or conflict with them.

processor_kwargs

Optional

Type: JSON object

Default: None

Provides advanced keyword arguments to the processor that prepares text, images, or video for the model. Use it for supported preprocessing options not exposed elsewhere, and avoid conflicting values because they can change resizing, tokenization, or media handling.