跳转到主要内容

AI models that run on this device.

Two small chat models run in a computer’s browser here; every other model is a file you download.

deepset

roberta-large-squad2

Can I run roberta-large-squad2 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.

roberta-large-squad2 is an open-weights language model for question answering. Model weights are learned parameters; a runtime loads them. A hosted file is an individual file Hugging Bay can serve. SHA-256 identifies exact file bytes. The availability date above applies to this file record, not the upstream metadata update date.

As of the recorded file availability check on .

Recorded SHA-256 for model.safetensors: 63ff07ecdc769a0a44051e261492f0e6b7827711aa723560d4435236a54ee708. Exact file evidence · Machine-readable source facts · Run evidence and any recorded receipts. A checksum fingerprints only the named file bytes; it does not prove safety, quality, a complete multi-file selection or a successful run.

Updated · Page-copy source revision 8871bab84e1cf80aea1686a944ec335078a6c036 · Source files: apps/web/lib/model-page-template.mjs, apps/web/lib/model-page-v3.mjs, apps/web/lib/aeo-page.mjs · Full revision record

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

deepset/roberta-large-squad2
Model details
question answeringLicense: cc-by-4.0SHA-256 recorded for 8 of 10 filessafetensors · BIN

Content controls: not assessed.

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

6 hosted of 10 listed

Hashes recorded. Date not recorded.

File大小SHA-256来源下载
Weights
model.safetensors Default1.42 GB
63ff07ec…a54ee70863ff07ecdc769a0a44051e261492f0e6b7827711aa723560d4435236a54ee708
Hosted下载
pytorch_model.bin1.42 GB
f0a98cec…09f90fc5f0a98cec67b9022abbcc667656745dd04a87e2c56d07d8f5175df22b09f90fc5
Upstream onlyFile metadata
Tokenizer & config
config.json696 bytes
edf4c5d8…b2634c75edf4c5d8b8b263deb333759d960cdb60f30010f4c38fd9c79836b4a3b2634c75
Hosted下载
flax_model.msgpack1.42 GB
17d19dd0…a553b0cd17d19dd0f99103b4278204f0b76f680e8ae6be57586ead9c5e4291d1a553b0cd
Upstream onlyFile metadata
merges.txt456.4 KB
fe36cab2…82a95862fe36cab26d4f4421ed725e10a2e9ddb7f799449c603a96e7f29b5a3c82a95862
Hosted下载
tokenizer_config.json1.19 KB
ce3be704…65a11031ce3be704b2b7dab64ec8b98abb9996d3dcbe8a845b24520d381d17a765a11031
Hosted下载
vocab.json798.3 KB
ed19656e…3670ab5eed19656ea1707df69134c4af35c8ceda2cc9860bf2c3495026153a133670ab5e
Hosted下载
special_tokens_map.json239 bytes
378eb3bf…22ae554d378eb3bf733eb16e65792d7e3fda5b8a4631387ca04d2015199c4d4f22ae554d
Hosted下载
Docs
.gitattributes790 bytes—Upstream onlyFile metadata
README.md7.67 KB—Upstream onlyFile metadata

检查下载文件

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

macOS
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.