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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.

klue

roberta-large

Can I run roberta-large on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 5 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 is an open-weights language model for masked-language modeling. 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: e0c7520e0e5c5e6c0f8f6b0767574c51fd5cdfb332f28168ad6f1bb9d1b9716a. 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 .

klue/roberta-large
Model details
masked-language modelingLicense: unknownSHA-256 recorded for 6 of 9 filessafetensors · BIN

Content controls: not assessed.

The catalog lists this model for filling in missing words in text. Catalog sources: task, cardMetadata.pipelineTag.

5 hosted of 9 listed

Hashes recorded. Date not recorded.

FileGrößeSHA-256QuelleHerunterladen
Weights
model.safetensors Default1.35 GB
e0c7520e…d1b9716ae0c7520e0e5c5e6c0f8f6b0767574c51fd5cdfb332f28168ad6f1bb9d1b9716a
HostedHerunterladen
pytorch_model.bin1.35 GB
fd6ebf63…621b7876fd6ebf63041d35e4dd5f9676827c10bca5b63b77644e9da8bd24801b621b7876
Upstream onlyFile metadata
Tokenizer & config
config.json547 bytes
f1ee4dcb…e6dba552f1ee4dcbb2869197b1840074d17150a34ef4ae1fe1d4d65f83dc4dc3e6dba552
HostedHerunterladen
special_tokens_map.json173 bytes
2b2b6960…538df9422b2b6960db46dfc77be309404710b41541fb8f46596b9622f5456be4538df942
HostedHerunterladen
tokenizer.json751.5 KB
66ac6204…294f07d366ac6204e18a45fa724fca7d44bc5f450881aa4c34f6352ddf27ada2294f07d3
HostedHerunterladen
tokenizer_config.json375 bytes
2c869369…aa11cb9d2c869369e1420125b87876b036ef9715e6844e73dcabb65791e0f655aa11cb9d
HostedHerunterladen
vocab.txt248.5 KB—Upstream onlyFile metadata
Docs
.gitattributes744 bytes—Upstream onlyFile metadata
README.md1.37 KB—Upstream onlyFile metadata

Einen Download prüfen

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.