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

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

检查下载文件

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.

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