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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.

spicecloud

bert-yelp

Can I run bert-yelp 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.

bert-yelp is an open-weights language model for masked-language modeling. 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 .

Recorded SHA-256 for model.safetensors: 68d45e234eb4a928074dfd868cead0219ab85354cc53d20e772753c6bb9169d3. 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 · Page text: As of · Content revision

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

spicecloud/bert-yelp
Model details
masked-language modelingLicense: apache-2.0SHA-256 recorded for 8 of 12 filesBIN · safetensors

Content controls: not assessed.

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

5 hosted of 12 listed

Hashes recorded. Date not recorded.

FileGrößeSHA-256QuelleHerunterladen
Weights
model.safetensors Default440.4 MB
68d45e23…bb9169d368d45e234eb4a928074dfd868cead0219ab85354cc53d20e772753c6bb9169d3
HostedHerunterladen
coreml/fill-mask/float32_model.mlpackage/Data/com.apple.CoreML/weights/weight.bin531.8 MB
c0c9f491…f097e289c0c9f4914b4f0053785e96b8583cd59cda63c2f1b6e95a03970d772bf097e289
Upstream onlyFile metadata
pytorch_model.bin440.5 MB
09741738…a67b203a097417381d6c7230bd9e3557456d726de6e83245ec8b24f529f60198a67b203a
Upstream onlyFile metadata
Tokenizer & config
config.json570 bytes
7160e155…4f187d207160e1553ad2ca51d8c1cb066be533db31826e12d173824c1bb0cb1a4f187d20
HostedHerunterladen
coreml/fill-mask/float32_model.mlpackage/Data/com.apple.CoreML/model.mlmodel164.9 KB
59ebda1b…d940e99359ebda1b73ce46947d8e6be8b39f018aae7d6c4d5809537225fdaaadd940e993
Upstream onlyFile metadata
coreml/fill-mask/float32_model.mlpackage/Manifest.json617 bytes—Upstream onlyFile metadata
tokenizer_config.json28 bytes
53b6f42b…b4fc90e153b6f42b8b8daddbdc6d3532c324187a92b46c1602bd6e8d4ad5a413b4fc90e1
HostedHerunterladen
vocab.txt231.5 KB—Upstream onlyFile metadata
tokenizer.json466.1 KB
ce64fce7…0d8c9a98ce64fce797c24f68df90b40a3f74f579b336a493db14bd583fd520ea0d8c9a98
HostedHerunterladen
Docs
.gitattributes604 bytes—Upstream onlyFile metadata
LICENSE11.4 KB
43070e2d…5e1379c143070e2d4e532684de521b885f385d0841030efa2b1a20bafb76133a5e1379c1
HostedHerunterladen
README.md10.5 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.