hing-gpt
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l3cube-pune/hing-gptQuick answer: compatibility and sources
Can I run hing-gpt 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.
hing-gpt is an open-weights language model for text generation. 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: d015969dbad6c6e9887e7b1f2c71fff3c203590b1b351d4f7b0be4c2838c37d1. 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-l3cube-pune-hing-gpt.
- Open /artifact/hf-model-l3cube-pune-hing-gpt/files for this exact filenames, availability and any recorded SHA-256.
- Open /evidence/artifacts/hf-model-l3cube-pune-hing-gpt for run-readiness evidence tied to that record; absent receipts stay unmeasured.
- Open /api/artifacts/hf-model-l3cube-pune-hing-gpt/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.
6 hosted of 8 listed
Hashes recorded. Date not recorded.
| File | Size | SHA-256 | Source | Download |
|---|---|---|---|---|
| Weights | ||||
model. | 510.4 MB |
| Hosted | Download |
pytorch_ | 510.4 MB |
| Upstream only | File metadata |
| Tokenizer & config | ||||
config. | 958 bytes |
| Hosted | Download |
special_ | 2 bytes |
| Hosted | Download |
tokenizer. | 1.15 MB |
| Hosted | Download |
tokenizer_ | 46 bytes |
| Hosted | Download |
| Docs | ||||
. | 1.23 KB | — | Upstream only | File metadata |
README. | 1.79 KB |
| Hosted | Download |
Check a download
In the folder where you saved README.md, run:
shasum -a 256 -- 'README.md'
sha256sum -- 'README.md'
Get-FileHash -LiteralPath 'README.md' -Algorithm SHA256
Compare the result with the recorded SHA-256.