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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.

deepset

gelectra-base-generator

Can I run gelectra-base-generator on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 4 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.

gelectra-base-generator 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: ca93eeb65cf2e2bd6647c383af630a9d10f9a064f43bd3fdb667e47b276c6e2d. 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/gelectra-base-generator
Model details
masked-language modelingLicense: mitSHA-256 recorded for 6 of 8 filessafetensors · BIN · H5

Content controls: not assessed.

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

4 hosted of 8 listed

Hashes recorded. Date not recorded.

FileGrößeSHA-256QuelleHerunterladen
Weights
model.safetensors Default136.8 MB
ca93eeb6…276c6e2dca93eeb65cf2e2bd6647c383af630a9d10f9a064f43bd3fdb667e47b276c6e2d
HostedHerunterladen
pytorch_model.bin136.8 MB
129b4086…dc84c86d129b408665ba892cdb4deca2e45e442e0b7cd46f852247bcd22462d0dc84c86d
Upstream onlyFile metadata
Tokenizer & config
config.json582 bytes
93e3934d…ad3d767e93e3934de533e5daa385cb7187f37733333fabd611c2b8b886d49d74ad3d767e
HostedHerunterladen
tf_model.h5234.2 MB
00bada43…23e401b700bada437ce1da08b345ff7270fd9f3901d9559e7ca43bde61bc895623e401b7
Upstream onlyFile metadata
tokenizer_config.json83 bytes
25f2b98f…dca1037825f2b98fcd4c39add7f30fa8e129c9d7d1fc2d27a37d615ae6452a47dca10378
HostedHerunterladen
vocab.txt239.8 KB
bf186f7f…f13039a3bf186f7fb9cb667d811c08b45ce64d1e8e262277bb053f05d1aef3e9f13039a3
HostedHerunterladen
Docs
.gitattributes399 bytes—Upstream onlyFile metadata
README.md3.03 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.