Stable-DiffCoder-8B-Base safetensors download | Hugging Bay

Q: What is this model?

ByteDance-Seed/Stable-DiffCoder-8B-Base is an open-weights language model for text generation published by ByteDance-Seed, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for text generation: ByteDance-Seed/Stable-DiffCoder-8B-Base · 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?

ByteDance-Seed/Stable-DiffCoder-8B-Base has 8B parameters. Hosted here: 10 files, 16.5 GB. Full repo upstream: 16.5 GB. The recommended download, a 4-file weight set, is 16.5 GB.

Q: What can I download here?

Hosted here: 10 files, 16.5 GB. Full repo upstream: 16.5 GB. The original release is at https://huggingface.co/ByteDance-Seed/Stable-DiffCoder-8B-Base.

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-bytedance-seed-stable-diffcoder-8b-base/safety on Hugging Bay.

Q: Will ByteDance-Seed/Stable-DiffCoder-8B-Base 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.

ByteDance-Seed

Stable-DiffCoder-8B-Base

ByteDance-Seed/Stable-DiffCoder-8B-Base

Model details

text generationLicense: mitSHA-256 recorded for 11 of 13 filessafetensors

Content controls: not assessed.

Listed for generating text; for developers building text generation tools. Catalog sources: license, cardMetadata.license, task, cardMetadata.pipelineTag.

View as JSON →

10 hosted of 13 listed

Hashes recorded. Date not recorded.

File	Tamanho	SHA-256	Origem	Baixar
Weights
`model-00001-of-00004.safetensors`	4.92 GB	`ed279541…86686bc0` `ed279541b5d4a6dfa50913b9cb9b268a79b9eb37f672e336a05f18c586686bc0`	Hosted	Baixar
`model-00002-of-00004.safetensors`	4.92 GB	`0c3342e1…7acbae5a` `0c3342e1e2b285ba21a8ed28310a18840aa12f18642b6fd19677308b7acbae5a`	Hosted	Baixar
`model-00003-of-00004.safetensors`	5 GB	`6b6c5e15…e26e06e4` `6b6c5e15d70de98a015cacbaab4c10ca01527893ed5200095cd3941de26e06e4`	Hosted	Baixar
`model-00004-of-00004.safetensors`	1.66 GB	`6499ae44…6f4493b2` `6499ae443f6c54d23f4b752a4cd426d7cdf6ce40f812454aca9696866f4493b2`	Hosted	Baixar
Tokenizer & config
`config.json`	845 bytes	`74cffa0c…b4c94d6e` `74cffa0ca4ecc72d9de1e2c982fd1dc0fdb9d988ed9dbcf221b31dfeb4c94d6e`	Hosted	Baixar
`imgs/intro_performance.png`	114.4 KB	`b3936701…5ee9a7bf` `b3936701225ed300472efa594ddc153dbbb3dce4cf79aff8a5221fb15ee9a7bf`	Upstream only	File metadata
`model.safetensors.index.json`	23.9 KB	`08839bef…569d831b` `08839befe0a1d5dc6762109dcc9395579f45679905f7fa2eaab73045569d831b`	Hosted	Baixar
`modeling_stable_diffcoder.py`	10 KB	—	Upstream only	File metadata
`special_tokens_map.json`	760 bytes	`4c0be99b…d96ae158` `4c0be99bc70d51bf5cec2f9fbc2eb7bea3f0b4439ddd74f71065683fd96ae158`	Hosted	Baixar
`tokenizer.json`	11.9 MB	`2c9765e3…2c4dac6d` `2c9765e3f23ba5809c82adcaf0851d83f6b294f2503f6956fcaa31f62c4dac6d`	Hosted	Baixar
`tokenizer_config.json`	27.9 KB	`1c5b073e…a2d3be26` `1c5b073e62364ef1120829b77277c8efcfbe6f1817688047b155a7cda2d3be26`	Hosted	Baixar
Docs
`.gitattributes`	1.63 KB	—	Upstream only	File metadata
`README.md`	8.6 KB	`ae43fb61…177527d2` `ae43fb613d70ed5ff7f12d227e5f679d8d600dc18593126b9d3aa550177527d2`	Hosted	Baixar

Verificar um download

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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