Tasks and inputs
google/owlv2-large-patch14-finetuned is listed for Zero-shot object detection. It accepts image, text and produces bounding boxes. Use the publisher’s input format and preprocessing for your chosen deployment.
SyncDev model directory · Profile updated Oct 7, 2026
google/owlv2-large-patch14-finetuned is a source-linked Hugging Face repository assigned to Zero-shot object detection. Its recorded task interface accepts image, text and produces bounding boxes.
The specification score summarizes recorded features and limits. It is not a benchmark result.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
google/owlv2-large-patch14-finetuned is a Hugging Face repository returned by the public Zero-shot object detection task feed. Its recorded download count is 778 and it has 6 likes when the repository snapshot was collected. Popularity is useful for discovery, but it is not a performance ranking or a guarantee of suitability.
This record is categorized for Zero-shot object detection. A task category describes the intended machine-learning problem; it does not prove that every version, checkpoint, quantization, or deployment method produces the same quality. Teams should read the model card and test representative inputs before choosing it.
The public repository lists transformers as its library metadata. Its recorded tags include transformers, pytorch, owlv2, zero-shot-object-detection, vision, arxiv:2306.09683, license:apache-2.0, region:us. These source details are retained so readers can trace this directory entry back to the repository instead of relying on copied descriptions.
Measure missed objects, false positives and localization at several IoU thresholds. Include small, overlapping and partially hidden objects; record input resolution and preprocessing.
The Hugging Face task assignment records image, text as input and bounding boxes as output for google/owlv2-large-patch14-finetuned. This interface summary comes from the repository’s recorded Zero-shot object detection task classification. It helps readers distinguish a text, image, audio, video, document, embedding, or prediction workflow without inferring undocumented API behavior. Model wrappers can expose different preprocessing and response formats, so verify the upstream model card and the exact runtime before deployment.
Explore google models and the zero-shot object detection collection. Use the comparison tool to inspect a second candidate.
Compare the model on the work you need to complete.
google/owlv2-large-patch14-finetuned is listed for Zero-shot object detection. It accepts image, text and produces bounding boxes. Use the publisher’s input format and preprocessing for your chosen deployment.
Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
Use the model identifier and account requirements for the selected API route. Confirm its request limits and output format with one complete task before connecting a larger workflow.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
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fushh7/llmdet_swin_tiny_hf is a source-linked Hugging Face repository assigned to Zero-shot object detection. Its recorded task interface accepts image, text and produces bounding boxes.
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google/owlv2-base-patch16-ensemble is a source-linked Hugging Face repository assigned to Zero-shot object detection. Its recorded task interface accepts image, text and produces bounding boxes.
google/owlv2-base-patch16-finetuned is a source-linked Hugging Face repository assigned to Zero-shot object detection. Its recorded task interface accepts image, text and produces bounding boxes.
google/owlv2-large-patch14 is a source-linked Hugging Face repository assigned to Zero-shot object detection. Its recorded task interface accepts image, text and produces bounding boxes.