SqueezeBert-Context-based-QA download | Hugging Bay

Q: What is this model?

DracolIA/SqueezeBert-Context-based-QA is an open-weights language model for question answering published by DracolIA, added to Hugging Bay Sep 25, 2026. Model from Hugging Face for question answering: DracolIA/SqueezeBert-Context-based-QA · transformers

Q: Can I use it commercially?

It is released under the apache-2.0 license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

Hosted here: at least 5 listed files; full count and size unknown. Full repo upstream: 205.4 MB. The recommended download, model.safetensors, is 204.4 MB.

Q: What can I download here?

Hosted here: at least 5 listed files; full count and size unknown. Full repo upstream: 205.4 MB. The original release is at https://huggingface.co/DracolIA/SqueezeBert-Context-based-QA.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 5 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-dracolia-squeezebert-context-based-qa/safety on Hugging Bay.

Q: Will DracolIA/SqueezeBert-Context-based-QA 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.

DracolIA

SqueezeBert-Context-based-QA

DracolIA/SqueezeBert-Context-based-QA

Model details

question answeringLicense: apache-2.0SHA-256 recorded for 6 of 9 filessafetensors · BIN

Content controls: not assessed.

Listed for answering questions; for developers building question answering tools. Catalog sources: license, cardMetadata.license, task, cardMetadata.pipelineTag.

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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-dracolia-squeezebert-context-based-qa/model.safetensors",
    "model.safetensors",
)

Other ways

Run it on your computerOpen in Hugging Bay appSend to a computerApp links support one GGUF file.

5 hosted of 9 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors204 MB · 1 file Download · 204 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

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

5 hosted of 9 listed

Hashes recorded. Date not recorded.

File	Taille	SHA-256	Source	Télécharger
Weights
`model.safetensors` Default	204.4 MB	`092622d7…66200c03` `092622d7b43b9b802a09c82032479c28f5fdc720b6c9f45fca8c9f2066200c03`	Hosted	Télécharger
`training_args.bin`	4.86 KB	`852ba888…c55343b3` `852ba888e1d1a958b6233a4c81e7a9887192d6ddd274e2334c5ea440c55343b3`	Upstream only	File metadata
Tokenizer & config
`config.json`	730 bytes	`6aed6b72…f1adcb42` `6aed6b72cd6cc11dca404b193c3e60af153ec030ce43235c5bc7f93cf1adcb42`	Hosted	Télécharger
`tokenizer.json`	711.6 KB	`828f0382…afeef752` `828f0382799b478c8aae48d22a48a0b3a6c8703ea6ad3f17b0a54527afeef752`	Hosted	Télécharger
`tokenizer_config.json`	1.2 KB	`8f2fbf9d…6f35648e` `8f2fbf9d66e0a4eef446cb69c29418f699679742d514f97353a520be6f35648e`	Hosted	Télécharger
`vocab.txt`	231.6 KB	—	Upstream only	File metadata
`special_tokens_map.json`	125 bytes	`b6d346be…76237ee3` `b6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3`	Hosted	Télécharger
Docs
`.gitattributes`	1.52 KB	—	Upstream only	File metadata
`README.md`	275 bytes	—	Upstream only	File metadata

Vérifier un téléchargement

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

Compare the result with the recorded SHA-256.

SqueezeBert-Context-based-QA

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