jinmang2

kpfbert

Search / embeddings

This receipt records checks for this exact file; it does not prove safety or that it will run on your device. Read the receipt

Model details
text embeddingsLicense: unknownSHA-256 recorded for 6 of 8 filessafetensors · BIN
Quick answer: compatibility and sources

Can I run kpfbert 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.

kpfbert 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: f145622431658b1c6b6cb4c9d54b810a3b183875b22b465177f7e267a6dc68d1. 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-jinmang2-kpfbert.
  • Open /artifact/hf-model-jinmang2-kpfbert/files for this exact filenames, availability and any recorded SHA-256.
  • Open /evidence/artifacts/hf-model-jinmang2-kpfbert for run-readiness evidence tied to that record; absent receipts stay unmeasured.
  • Open /api/artifacts/hf-model-jinmang2-kpfbert/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.

Requirements and source record
jinmang2/kpfbert

Content controls: not assessed.

The catalog lists this model for finding useful details in data. Catalog sources: task, cardMetadata.pipelineTag.

Model from Hugging Face for feature extraction: jinmang2/kpfbert · transformers

Default download
Availability unknown
Parameters
Not listed
Context
Not listed
Format
safetensors · BIN

Will it run on my computer?

File size is a starting point. Memory and runtime support also matter.

Check this model on my computer

Files

.gitattributes

Hash not recorded

Size not listedView file
README.md

Hash not recorded

Size not listedView file
config.json

SHA-256 recorded

Size not listedView file
model.safetensors

SHA-256 recorded

454 MBView file
pytorch_model.bin

SHA-256 recorded

454 MBView file
All files and download checks →
Where this information comes from

क्या शामिल है

5 hosted of 8 listed

Weights
Tokenizer & config
README, LICENSE & .gitattributes

इस मॉडल के बारे में

External Hugging Face catalog record for jinmang2/kpfbert. Task: feature extraction. Library: transformers. Popularity signal at import: 16,906 downloads and 4 likes.

ज़रूरी जानकारी

Hosted here
5 hosted of 8 listed
Full repo upstream
907.9 MB
Format
safetensors · BIN
File hashes
Hashes recorded. Date not recorded.

लाइसेंस और स्रोत

License: unknown

5 hosted of 8 listed

No license was found in metadata, the LICENSE file or README. Check the terms before you use or share the files.

See the JSON record →

License
unknown
Task
text embeddings
Hosted here
at least 5 listed files; full count and size unknown
Full repo upstream
907.9 MB
Files
5 hosted of 8 listed
Added to Hugging Bay
Updated at source
Source
jinmang2/kpfbert

FAQ

What is this model?

jinmang2/kpfbert is an embedding model for text embeddings published by jinmang2, added to Hugging Bay Sep 21, 2026. Model from Hugging Face for feature extraction: jinmang2/kpfbert · transformers

Can I use it commercially?

License: unknown. Check the upstream license text or ask the model author before commercial use.

How big is it?

Hosted here: at least 5 listed files; full count and size unknown. Full repo upstream: 907.9 MB.

What can I download here?

Hosted here: at least 5 listed files; full count and size unknown. Full repo upstream: 907.9 MB.

File checks and computer fit
File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 5 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-jinmang2-kpfbert/safety on Hugging Bay.

Will jinmang2/kpfbert run on my computer?

We can’t check the fit; we don’t know your machine. We don’t have your machine’s specs, so no check ran and no verdict is shown. Answer two quick questions and we’ll estimate, from the memory you tell us, whether it fits your machine. Or skip it; you can still download; fit isn’t checked.

jinmang2/kpfbertView as JSON →

Content controls: not assessed.

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