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Dpt Dinov2 Base Kitti

with ONNX weights to be compatible with Transformers.js.

KindOtherBase modelfacebook/dpt-dinov2-base-kittiVersionRevision 398ca4dCgrade

Model source

Kind
Other
File size
88.8–423 MB
Base model
facebook/dpt-dinov2-base-kitti
Version
vRevision 398ca4d
Updated
Nov 1, 2026
Downloads
15
Source
Hugging Face

Source description

https://huggingface.co/facebook/dpt-dinov2-base-kitti with ONNX weights to be compatible with Transformers.js.

Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).

Sources

1 source
Hugging FacePrimaryVersion 398ca4dc1a3e1b1984662d5034d834dcf4e85c7d
huggingface.co/onnx-community/dpt-dinov2-base-kitti/tree/398ca4dc1a3e1b1984662d5034d834dcf4e85c7d

Verified Nov 1

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Repository files

File inventory only; completeness is unverified.

Model artifacts

8 artifacts

onnx/model_bnb4.onnx

onnx · 129 MB · SHA-256 35619a6091f8…5593 · Hugging Face

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onnx/model_fp16.onnx

onnx · FP16 (unverified) · 212 MB · SHA-256 9d9f786ea7e5…2770 · Hugging Face

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onnx/model_int8.onnx

onnx · INT8 (unverified) · 111 MB · SHA-256 46761147fa44…8aaf · Hugging Face

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onnx/model_q4.onnx

onnx · Q4 (unverified) · 134 MB · SHA-256 6803c87d85a6…71fc · Hugging Face

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onnx/model_q4f16.onnx

onnx · 88.8 MB · SHA-256 8d36c56bb3e2…e42b · Hugging Face

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onnx/model_quantized.onnx

onnx · 111 MB · SHA-256 cc13c2d8dcb5…bb19 · Hugging Face

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onnx/model_uint8.onnx

onnx · UINT8 (unverified) · 111 MB · SHA-256 cc13c2d8dcb5…bb19 · Hugging Face

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onnx/model.onnx

onnx · 423 MB · SHA-256 60fb10011700…207c · Hugging Face

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Source excerpts

3 excerpts

--- base_model: facebook/dpt-dinov2-base-kitti library_name: transformers.js --- https://huggingface.co/facebook/dpt-dinov2-base-kitti with ONNX weights to be compatible with Transformers.js. Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).

Source context: 15 downloads · 0 likes · Pipeline depth-estimation · Library transformers.js · Repo onnx-community/dpt-dinov2-base-kitti

Source context: 7 downloads · 0 likes · Pipeline depth-estimation · Library transformers.js · Repo onnx-community/dpt-dinov2-base-kitti