Gemma-2B-Finetuined-pythonCode download | Hugging Bay

Q: What is this model?

Mr-Vicky-01/Gemma-2B-Finetuined-pythonCode is an open-weights language model for text generation published by Mr-Vicky-01, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for text generation: Mr-Vicky-01/Gemma-2B-Finetuined-pythonCode · transformers

Q: Can I use it commercially?

It is released under the mit license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

Mr-Vicky-01/Gemma-2B-Finetuined-pythonCode has 2B parameters. Hosted here: at least 10 listed files; full count and size unknown. Full repo upstream: 5.03 GB.

Q: What can I download here?

Hosted here: at least 10 listed files; full count and size unknown. Full repo upstream: 5.03 GB. The original release is at https://huggingface.co/Mr-Vicky-01/Gemma-2B-Finetuined-pythonCode.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 10 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-mr-vicky-01-gemma-2b-finetuined-pythoncode/safety on Hugging Bay.

Q: Will Mr-Vicky-01/Gemma-2B-Finetuined-pythonCode 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.

Mr-Vicky-01

Gemma-2B-Finetuined-pythonCode

Can I run Gemma-2B-Finetuined-pythonCode 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.

Gemma-2B-Finetuined-pythonCode 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 2026-10-22.

Recorded SHA-256 for model-00001-of-00002.safetensors: c7dd71e1d279c8eb98815ed07cd4d52437fbb1b425815da30961325733c9164b. 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 2026-10-21 · 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 2026-08-29 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

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Mr-Vicky-01/Gemma-2B-Finetuined-pythonCode

Model details

text generationLicense: mitSHA-256 recorded for 10 of 11 filessafetensors

Content controls: not assessed.

The catalog lists this model for working with code. Catalog sources: license, cardMetadata.license, tags, task, cardMetadata.pipelineTag.

View as JSON →

10 hosted of 11 listed

Hashes recorded. Date not recorded.

File	Größe	SHA-256	Quelle	Herunterladen
Weights
`model-00001-of-00002.safetensors`	4.95 GB	`c7dd71e1…33c9164b` `c7dd71e1d279c8eb98815ed07cd4d52437fbb1b425815da30961325733c9164b`	Hosted	Herunterladen
`model-00002-of-00002.safetensors`	67.1 MB	`d1e731ac…05c94eef` `d1e731acc65333e9034c1557c9a703937ed8bebe68efc48a89e4353b05c94eef`	Hosted	Herunterladen
Tokenizer & config
`config.json`	683 bytes	`71ee8f5a…45836aa7` `71ee8f5a145de3943a56d597a13e48eaea8a7bdfeabac9019248873445836aa7`	Hosted	Herunterladen
`generation_config.json`	132 bytes	`d8ecf66b…ee76467f` `d8ecf66b6421d0526fca308ac036772e418db7eb9de3c3abb82b84c2ee76467f`	Hosted	Herunterladen
`model.safetensors.index.json`	13.5 KB	`1b329486…cbf1a15a` `1b32948684e244670c6d7c9a9dc723bce5d4b2b34319879c9c1844a0cbf1a15a`	Hosted	Herunterladen
`tokenizer.json`	17.5 MB	`36da1831…2c9807c8` `36da1831627311242422cdbafc0308f7a49dcbab0ebf9eb8803a0ca42c9807c8`	Hosted	Herunterladen
`tokenizer.model`	4.24 MB	`61a7b147…e1d4c8e2` `61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2`	Hosted	Herunterladen
`tokenizer_config.json`	1.11 KB	`6d755ca2…b2ffc6a5` `6d755ca256041dd61c4f2932240310bed769c66f3fd54fa277f962a7b2ffc6a5`	Hosted	Herunterladen
`special_tokens_map.json`	441 bytes	`ac9fefa3…08cb993e` `ac9fefa3de2483df8199f386170016de76d6c060a3b72f834ac91c3908cb993e`	Hosted	Herunterladen
Docs
`.gitattributes`	1.57 KB	—	Upstream only	File metadata
`README.md`	2.73 KB	`8ba5d0cb…37cfc302` `8ba5d0cb1ea4c8e3b3d8178bac89d744eeaa65b124d47a044e5defed37cfc302`	Hosted	Herunterladen

Einen Download prüfen

In the folder where you saved README.md, run:

macOS

shasum -a 256 -- 'README.md'

Linux

sha256sum -- 'README.md'

Windows

Get-FileHash -LiteralPath 'README.md' -Algorithm SHA256

Compare the result with the recorded SHA-256.

Gemma-2B-Finetuined-pythonCode

Can I run Gemma-2B-Finetuined-pythonCode on my computer?

Einen Download prüfen

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