OPDLM-4B safetensors download | Hugging Bay

Q: What is this model?

divelab/OPDLM-4B is an open-weights language model for text generation published by divelab, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for text generation: divelab/OPDLM-4B · 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?

divelab/OPDLM-4B has 4B parameters. Hosted here: at least 13 listed files; full count and size unknown. Full repo upstream: 8.06 GB.

Q: What can I download here?

Hosted here: at least 13 listed files; full count and size unknown. Full repo upstream: 8.06 GB. The original release is at https://huggingface.co/divelab/OPDLM-4B.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 13 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-divelab-opdlm-4b/safety on Hugging Bay.

Q: Will divelab/OPDLM-4B 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.

divelab

OPDLM-4B

divelab/OPDLM-4B

Model details

text generationLicense: mitSHA-256 recorded for 13 of 18 filessafetensors

Content controls: not assessed.

Listed for chat; for developers building conversational tools. Catalog sources: license, cardMetadata.license, baseModel, tags, task, cardMetadata.pipelineTag.

View as JSON →

13 hosted of 18 listed

Hashes recorded. Date not recorded.

File	Size	SHA-256	Source	Download
Weights
`model-00001-of-00002.safetensors`	4.97 GB	`1091d773…91b83bbf` `1091d773e0ee7351f1224bafbe3592620273886fe9c426f2ad71275991b83bbf`	Hosted	Download
`model-00002-of-00002.safetensors`	3.08 GB	`835729ae…b7434338` `835729aea0a2e87604a0456eb9b1b4ea00c206bd9bf298451236ebdbb7434338`	Hosted	Download
Tokenizer & config
`added_tokens.json`	729 bytes	`321e1bf3…ecf23e68` `321e1bf30087d5b410aa5b76677941f614da428e5da1085a6523f121ecf23e68`	Hosted	Download
`config.json`	1.6 KB	`debc5d8a…f44a7a32` `debc5d8abfc0eda7706aa935cd1f18d9f8d63d8bce68cddd4dc19d89f44a7a32`	Hosted	Download
`configuration_qwen2.py`	10.8 KB	—	Upstream only	File metadata
`generation_config.json`	121 bytes	`5d3c1b12…5fc74dee` `5d3c1b12ce6fece499a9fbadf05cd4adf133c616cba0fefd86cb6f1d5fc74dee`	Hosted	Download
`merges.txt`	1.67 MB	`8831e4f1…08a904d5` `8831e4f1a044471340f7c0a83d7bd71306a5b867e95fd870f74d0c5308a904d5`	Hosted	Download
`model.safetensors.index.json`	32.8 KB	`e36bba5a…6495921a` `e36bba5af4706cfd22ecf7eedb5fd8f4d2559b92f2414b932651b9ed6495921a`	Hosted	Download
`modeling_qwen2.py`	42.7 KB	—	Upstream only	File metadata
`special_tokens_map.json`	755 bytes	`578e6ec6…62ab4046` `578e6ec616e5ab25f3f33a2b8cfda08f17b6f28462936ab09a5cfdd762ab4046`	Hosted	Download
`tokenization_qwen2.py`	13.9 KB	—	Upstream only	File metadata
`tokenization_qwen2_fast.py`	5.22 KB	—	Upstream only	File metadata
`tokenizer.json`	11.4 MB	`37578395…38968bbc` `37578395e36d9b7cf7fc87a3cc562f03fc7c2b9d480b3780c18ccbb838968bbc`	Hosted	Download
`tokenizer_config.json`	5.71 KB	`451e793d…774a959a` `451e793df784738571e96c6fa2aa129d4243df00bc6be320af0de407774a959a`	Hosted	Download
`vocab.json`	2.78 MB	`ca10d7e9…b1440910` `ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910`	Hosted	Download
`chat_template.jinja`	4.17 KB	`a55ee1b1…cf1974d8` `a55ee1b1660128b7098723e0abcd92caa0788061051c62d51cbe87d9cf1974d8`	Hosted	Download
Docs
`.gitattributes`	1.57 KB	—	Upstream only	File metadata
`README.md`	1.99 KB	`32ebc85a…9ba9b31f` `32ebc85aca2d4605bf7d693c5d306fba3345d97a8cfcf0dbac3bd49b9ba9b31f`	Hosted	Download

Check a 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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