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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.

Singaraj

sante-embed

Singaraj/sante-embed
Model details
text embeddingsLicense: apache-2.0SHA-256 recorded for 10 of 17 filessafetensors

Content controls: not assessed.

The catalog lists this model for turning text into vectors. Catalog sources: license, cardMetadata.license, cardMetadata.libraryName, modality, task, cardMetadata.pipelineTag.

Quick answer: compatibility and sources

Can I run sante-embed on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 10 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.

sante-embed is an embedding model for text embeddings. 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: af0addec53ab2cc8038aefa7a290aa9c6def2b0240dd747484acd8ba81c371d7. 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 .

Key facts

Catalog record
Summarizes upstream metadata; it is not itself a download or run receipt.
File evidence
Lists exact filenames, availability and any recorded SHA-256 for individual files.
Run evidence
Reports measured results only when a receipt exists for named file bytes and a setup; otherwise unmeasured.
Checksum scope
SHA-256 fingerprints one file’s bytes; it does not prove safety, quality or a multi-file bundle.

Evidence you can inspect (plain text)

  • This page’s quick answer names the file record for hf-model-singaraj-sante-embed.
  • Open /artifact/hf-model-singaraj-sante-embed/files for this exact filenames, availability and any recorded SHA-256.
  • Open /evidence/artifacts/hf-model-singaraj-sante-embed for run-readiness evidence tied to that record; absent receipts stay unmeasured.
  • Open /api/artifacts/hf-model-singaraj-sante-embed/card.md for machine-readable source facts (not a runtime test).
  • A matching checksum on this page fingerprints only the named bytes shown in file evidence.

Unmeasured states are stated explicitly; this page does not invent run scores or compatibility guarantees.

Which date applies to which fact

  • File availability check:
  • Committed page-copy sources:
  • Upstream model metadata: Dates on artifact records when shown; not implied by page-copy revision
  • Run receipts: Only on /evidence pages when recorded; otherwise unmeasured

Page-copy revision (Updated line above) identifies committed text sources, not upstream model edits or test outcomes.

10 hosted of 17 listed

Hashes recorded. Date not recorded.

FileGrößeSHA-256QuelleHerunterladen
Weights
model.safetensors3.09 GB
af0addec…81c371d7af0addec53ab2cc8038aefa7a290aa9c6def2b0240dd747484acd8ba81c371d7
HostedHerunterladen
Tokenizer & config
1_Pooling/config.json96 bytes—Upstream onlyFile metadata
added_tokens.json80 bytes
6a475432…ee54a5006a475432c61f8d6154d10d28c37671a36e5717daf3d15002a988968fee54a500
HostedHerunterladen
chat_template.jinja196 bytes
153280e3…39db80f3153280e3ff55d19da1398bdb3914ee2a51b80429bfaedde11d7d216c39db80f3
HostedHerunterladen
config.json1.55 KB
f0027f26…c124e7eef0027f2683923b327929ee4054a22c726b690daf8e41b78b622ecc42c124e7ee
HostedHerunterladen
config_sentence_transformers.json377 bytes
102ec413…f174ebbd102ec413dd51904ab841dd90c082878d6fd2c04781989e19ae85fb82f174ebbd
HostedHerunterladen
merges.txt1.67 MB—Upstream onlyFile metadata
modeling_qwen.py65.4 KB—Upstream onlyFile metadata
modules.json429 bytes
fa7d796a…c90f459cfa7d796a215e1b2416773062891923b191fc5a4849bc44e322997433c90f459c
HostedHerunterladen
sentence_bert_config.json241 bytes
30841640…ad186fc83084164002c0bca01b0259c5327123803fce32e660a57feb93184ffead186fc8
HostedHerunterladen
special_tokens_map.json370 bytes
daf48284…d9fb6af2daf48284de8f4779b1dbf20963a68180002fba2a34a5da72292380c5d9fb6af2
HostedHerunterladen
tokenization_qwen.py10.8 KB—Upstream onlyFile metadata
tokenizer.json11.4 MB
2f79052d…2fa65a202f79052deba517b0663d877714e117a31a4a6243cddb85fc4443c80a2fa65a20
HostedHerunterladen
tokenizer_config.json1.11 KB
6dcb9750…c6b46d916dcb9750e05232031a0baf63622f69861889769a7aa0dc5333652f54c6b46d91
HostedHerunterladen
vocab.json2.78 MB—Upstream onlyFile metadata
Docs
.gitattributes1.57 KB—Upstream onlyFile metadata
README.md5.58 KB—Upstream onlyFile metadata

Einen Download prüfen

In the folder where you saved added_tokens.json, run:

macOS
shasum -a 256 -- 'added_tokens.json'
Linux
sha256sum -- 'added_tokens.json'
Windows
Get-FileHash -LiteralPath 'added_tokens.json' -Algorithm SHA256

Compare the result with the recorded SHA-256.

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