mdeberta-v3-base-squad2-onnx download | Hugging Bay

Q: What is this model?

dewdev/mdeberta-v3-base-squad2-onnx is an open-weights language model for question answering published by dewdev, added to Hugging Bay Sep 24, 2026. Model from Hugging Face for question answering: dewdev/mdeberta-v3-base-squad2-onnx · pytorch

Q: Can I use it commercially?

It is released under the mit license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

Hosted here: 6 files, 1.13 GB. Full repo upstream: 5.34 GB. The recommended download, model.safetensors, is 1.11 GB.

Q: What can I download here?

Hosted here: 6 files, 1.13 GB. Full repo upstream: 5.34 GB. The original release is at https://huggingface.co/dewdev/mdeberta-v3-base-squad2-onnx.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 6 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-dewdev-mdeberta-v3-base-squad2-onnx/safety on Hugging Bay.

Q: Will dewdev/mdeberta-v3-base-squad2-onnx run on my computer?

We can’t check the fit; we don’t know your machine. We don’t have your machine’s specs, so no check ran and no verdict is shown. Answer two quick questions and we’ll estimate, from the memory you tell us, whether it fits your machine. Or skip it; you can still download; fit isn’t checked.

dewdev

mdeberta-v3-base-squad2-onnx

Can I run mdeberta-v3-base-squad2-onnx on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 6 hosted files; check the file list for the exact selection. A file-size fit is an estimate, not a successful run or speed promise. Read the license before use.

mdeberta-v3-base-squad2-onnx is an open-weights language model for question answering. Model weights are learned parameters; a runtime loads them. Hosting files does not prove that a complete model runs.

As of the availability check on 2026-10-22.

Recorded SHA-256 for model.safetensors: 16675f4d0b1dcaa8ae44b9d8cd395c7c539de1d5ae06a7242389b195502ef3c2. File evidence · Machine-readable facts · Run evidence and any recorded receipts · Proof Lab measurement policy. A checksum verifies byte identity, not safety; this answer asserts no measured runtime result.

Updated 2026-10-21 · Page text: As of 2026-10-21 · Content revision

Model metadata: As of 2026-09-24 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

dewdev/mdeberta-v3-base-squad2-onnx

Model details

question answeringLicense: mitSHA-256 recorded for 14 of 17 filessafetensors · ONNX · BIN

Content controls: not assessed.

The catalog lists this model for answering questions. Catalog sources: license, cardMetadata.license, task, cardMetadata.pipelineTag.

View as JSON →

Your next step

Use it from code

This Python snippet downloads the selected file. Running the model needs its own library and setup.

from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-dewdev-mdeberta-v3-base-squad2-onnx/model.safetensors",
    "model.safetensors",
)

Other ways

This file cannot open in the app. The app supports one GGUF file at a time.

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6 hosted of 17 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors1.11 GB · 1 file Download · 1.11 GB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

Compare your file’s SHA-256 with the recorded hash.

6 hosted of 17 listed

Hashes recorded. Date not recorded.

File	Size	SHA-256	Source	Download
Weights
`model.safetensors` Default	1.11 GB	`16675f4d…502ef3c2` `16675f4d0b1dcaa8ae44b9d8cd395c7c539de1d5ae06a7242389b195502ef3c2`	Hosted	Download
`onnx/model.onnx`	1.11 GB	`bda730f2…c1e7c393` `bda730f2d42c5bf0bb20077d13958b2be15020b20faafc6ffa01d4e2c1e7c393`	Upstream only	File metadata
`onnx/model_int16.onnx`	401.9 MB	`faf2466d…029909e1` `faf2466d109d0b5afe259bb03df373d958ff148714813ff92cc88fe7029909e1`	Upstream only	File metadata
`onnx/model_int4.onnx`	274.5 MB	`19cbd51a…e9b54747` `19cbd51af2bd96b7bdb70e62f0838eddc14a38ad42fe1e59a7ba4327e9b54747`	Upstream only	File metadata
`onnx/model_int8.onnx`	317 MB	`180ed88a…043a0363` `180ed88a1c7db8bb03655d68bcaedb9e313d0e4de8b018a9d49269c9043a0363`	Upstream only	File metadata
`onnx/model_uint16.onnx`	401.9 MB	`a5cdd168…f27069cb` `a5cdd168780dd3d3b3796be241823c28383342d36edc21f61118e4d9f27069cb`	Upstream only	File metadata
`onnx/model_uint4.onnx`	274.5 MB	`eedf1f45…9a687b4d` `eedf1f45a6dc74a80aee2b7dd1cbefe4e663063837bb33a2e5a6c8da9a687b4d`	Upstream only	File metadata
`onnx/model_uint8.onnx`	317 MB	`66590317…4c5b947a` `665903179f42cc28dd2d452b3d736c7541e8011307432947776d53d44c5b947a`	Upstream only	File metadata
`pytorch_model.bin`	1.11 GB	`91d05e57…82de2c56` `91d05e57e35a8a3768fbdbd26ecfa3c0672f6e889c0554e1859cabf282de2c56`	Upstream only	File metadata
Tokenizer & config
`added_tokens.json`	23 bytes	`fb697283…adc9155a` `fb697283833d25e2c711f1bc37730ecd8b20f4bd5f015db1d84aefe0adc9155a`	Hosted	Download
`config.json`	879 bytes	`37a58cdb…498174ee` `37a58cdb26f26ee9ec2ecd037159669c0aec28a015395c91f99736d5498174ee`	Hosted	Download
`special_tokens_map.json`	173 bytes	`311de3f4…bf519ecc` `311de3f4eed9d76a43bf0d71f10e62e086ca65ccce9f15d5da0d2098bf519ecc`	Hosted	Download
`to_onnx.py`	7.3 KB	—	Upstream only	File metadata
`tokenizer.json`	16.3 MB	`c6b52ff7…105497b7` `c6b52ff7043b8e7c0712d94ffa3c8a9c9522538157a11f5b59dd9051105497b7`	Hosted	Download
`tokenizer_config.json`	453 bytes	`2bd085c4…8989aa5c` `2bd085c40afa18e83c287df793b3a294ab3e6d5b27521aaed86b86658989aa5c`	Hosted	Download
Docs
`.gitattributes`	1.57 KB	—	Upstream only	File metadata
`README.md`	3.31 KB	—	Upstream only	File metadata

Check a download

In the folder where you saved model.safetensors, run:

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shasum -a 256 -- 'model.safetensors'

Linux

sha256sum -- 'model.safetensors'

Windows

Get-FileHash -LiteralPath 'model.safetensors' -Algorithm SHA256

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mdeberta-v3-base-squad2-onnx

Can I run mdeberta-v3-base-squad2-onnx on my computer?

Check a download

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