code-pruner safetensors download (1.35 GB) | Hugging Bay

Q: What is this model?

ayanami-kitasan/code-pruner is an open-weights language model for token classification published by ayanami-kitasan, added to Hugging Bay Jun 30, 2026. Model from Hugging Face: ayanami-kitasan/code-pruner

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?

Hosted here: at least 10 listed files; full count and size unknown. The full repository size is not recorded. The recommended download, model.safetensors, is 1.35 GB.

Q: What can I download here?

Hosted here: at least 10 listed files; full count and size unknown. Full repo upstream: unknown. The original release is at https://huggingface.co/ayanami-kitasan/code-pruner.

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-ayanami-kitasan-code-pruner/safety on Hugging Bay.

Q: Will ayanami-kitasan/code-pruner 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.

ayanami-kitasan

code-pruner

ayanami-kitasan/code-pruner

Model details

token classificationLicense: mitHashes recordedsafetensors

Content controls: not assessed.

Listed for labeling parts of text; for developers building token classifiers. Catalog sources: license, task.

View as JSON →

Your next step

Use it from code

This Python snippet downloads the selected file. Running the model needs its own library and setup.

from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-ayanami-kitasan-code-pruner/model.safetensors",
    "model.safetensors",
)

Other ways

10 hosted of 11 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors1.35 GB · 1 file Download · 1.35 GB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

Compare your file’s SHA-256 with the recorded hash.

10 hosted of 11 listed

Hashes recorded. Date not recorded.

File	大小	SHA-256	来源	下载
Weights
`model.safetensors` Default	1.35 GB	`373b77f5…413adae9` `373b77f5262c3298b803303d49ea38949d3e92f08dc3bbb90b03f490413adae9`	Hosted	下载
Tokenizer & config
`chat_template.jinja`	4.12 KB	`87a2728c…e33396b5` `87a2728cb8dc9fe424d624542f6060ec05a1d285ebbec578bb078900e33396b5`	Hosted	下载
`config.json`	463 bytes	`9b1e8873…7a080838` `9b1e88732190d3bb92b7a36b9b208011403c09cda3647c8fae0adaf87a080838`	Hosted	下载
`merges.txt`	1.67 MB	`8831e4f1…08a904d5` `8831e4f1a044471340f7c0a83d7bd71306a5b867e95fd870f74d0c5308a904d5`	Hosted	下载
`tokenizer_config.json`	5.4 KB	`443bfa62…f45f7fa0` `443bfa629eb16387a12edbf92a76f6a6f10b2af3b53d87ba1550adfcf45f7fa0`	Hosted	下载
`vocab.json`	2.78 MB	`ca10d7e9…b1440910` `ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910`	Hosted	下载
`added_tokens.json`	707 bytes	`c0284b58…0833c680` `c0284b582e14987fbd3d5a2cb2bd139084371ed9acbae488829a1c900833c680`	Hosted	下载
`special_tokens_map.json`	613 bytes	`76862e76…dd3a1ecd` `76862e765266b85aa9459767e33cbaf13970f327a0e88d1c65846c2ddd3a1ecd`	Hosted	下载
`tokenizer.json`	11.4 MB	`aeb13307…4492dae4` `aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4`	Hosted	下载
Docs
`README.md`	2.23 KB	`895dde38…6ad39f8c` `895dde384e3bf5ffdc2f1782cbd7a36994304452e93bcbed4ef88c256ad39f8c`	Hosted	下载
`.gitattributes`	0 bytes	—	Upstream only	File metadata

检查下载文件

In the folder where you saved model.safetensors, run:

macOS

shasum -a 256 -- 'model.safetensors'

Linux

sha256sum -- 'model.safetensors'

Windows

Get-FileHash -LiteralPath 'model.safetensors' -Algorithm SHA256

Compare the result with the recorded SHA-256.

code-pruner

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