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batmac

gradient-ai-text-detector-4bit

Can I run gradient-ai-text-detector-4bit 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.

gradient-ai-text-detector-4bit is an open-weights language model for text classification. 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: b6d34cd0e7f8744d9954f9594b320213ac847a399516182f79bf73f1b75504fe. 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 .

batmac/gradient-ai-text-detector-4bit
Model details
text classificationLicense: mitSHA-256 recorded for 7 of 13 filessafetensors

Content controls: not assessed.

The catalog lists this model for sorting text into categories. Catalog sources: license, cardMetadata.license, baseModel, task, cardMetadata.pipelineTag.

6 hosted of 13 listed

Hashes recorded. Date not recorded.

FileSizeSHA-256SourceDownload
Weights
model.safetensors Default698.7 MB
b6d34cd0…b75504feb6d34cd0e7f8744d9954f9594b320213ac847a399516182f79bf73f1b75504fe
HostedDownload
Tokenizer & config
config.json1.51 KB
265e2dd5…35b110e4265e2dd5ab7d76ed47a384652454ee29169ed3f27e727707ba46062335b110e4
HostedDownload
scripts/bench_quant.py3.73 KB—Upstream onlyFile metadata
scripts/eval_quant.py3.05 KB—Upstream onlyFile metadata
scripts/quantize.py3.22 KB—Upstream onlyFile metadata
special_tokens_map.json286 bytes
9463f61e…b92369b99463f61e1b109a8eb4688b829260d7c6b1e6dff04c98ff7269bb89e2b92369b9
HostedDownload
spm.model2.46 MB
c679fbf9…4af586fdc679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
Upstream onlyFile metadata
tokenizer.json8.34 MB
ccab0d2b…99829d59ccab0d2b1c2aec656e37e1f5a3bc8a71e64186f221717059852bfc1c99829d59
HostedDownload
tokenizer_config.json724 bytes
c8c1af52…91e06c62c8c1af527a2a116521e677904709cc09238219ec79cfa438984df47791e06c62
HostedDownload
added_tokens.json23 bytes
dc046d04…5ca4e91fdc046d04c9b0ada7ae6f1dc89c465801799acdf0c9a6aab8c15a1b2d5ca4e91f
HostedDownload
Docs
.gitattributes178 bytes—Upstream onlyFile metadata
README.md4.93 KB—Upstream onlyFile metadata
scripts/README.md1.38 KB—Upstream onlyFile metadata

Check a download

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.