LoopCoder-V2 safetensors download | Hugging Bay

Q: What is this model?

Multilingual-Multimodal-NLP/LoopCoder-V2 is an open-weights language model for text generation published by Multilingual-Multimodal-NLP, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for text generation: Multilingual-Multimodal-NLP/LoopCoder-V2 · transformers

Q: Can I use it commercially?

It is released under the apache-2.0 license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

Hosted here: 13 files, 15.2 GB. Full repo upstream: 15.2 GB. The recommended download, a 3-file weight set, is 15.2 GB.

Q: What can I download here?

Hosted here: 13 files, 15.2 GB. Full repo upstream: 15.2 GB. The original release is at https://huggingface.co/Multilingual-Multimodal-NLP/LoopCoder-V2.

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-multilingual-multimodal-nlp-loopcoder-v2/safety on Hugging Bay.

Q: Will Multilingual-Multimodal-NLP/LoopCoder-V2 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.

Multilingual-Multimodal-NLP

LoopCoder-V2

Try browser chat with a small demo model (a separate model; device support is checked before loading).

Multilingual-Multimodal-NLP/LoopCoder-V2

Model details

text generationLicense: apache-2.0SHA-256 recorded for 13 of 17 filessafetensors

Content controls: not assessed.

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

View as JSON →

13 hosted of 17 listed

Hashes recorded. Date not recorded.

File	आकार	SHA-256	स्रोत	डाउनलोड करें
Weights
`model-00001-of-00003.safetensors`	5.35 GB	`e59b0f49…2f8e7eec` `e59b0f4976e5cfd528cf131c0b91438ab76650c39ed84a970b5446792f8e7eec`	Hosted	डाउनलोड करें
`model-00002-of-00003.safetensors`	5.29 GB	`f5ae74ba…a53cde14` `f5ae74ba4eabc60dda9b4977508459876c4651a089d5be537781b564a53cde14`	Hosted	डाउनलोड करें
`model-00003-of-00003.safetensors`	4.59 GB	`59d6feb6…2ba5e040` `59d6feb64f8cdff68b6da8a4cbcea16855a0f671ac7f7b97082c945d2ba5e040`	Hosted	डाउनलोड करें
Tokenizer & config
`added_tokens.json`	613 bytes	`298ac6b9…8a617db6` `298ac6b957b34e7ded59561f8e8f807c5aad5b09dfd46cf20f4850788a617db6`	Hosted	डाउनलोड करें
`chat_template.jinja`	7.68 KB	`15d6c898…752fe24a` `15d6c898fc0e05ddbafbd582d815801036b02bc661403fc296c00ea3752fe24a`	Hosted	डाउनलोड करें
`config.json`	949 bytes	`b95302a5…047d9176` `b95302a5af03c9320dbc7131cfb639ba07c8a2140d4631e5c9279d03047d9176`	Hosted	डाउनलोड करें
`configuration_iquestcoder.py`	8.98 KB	—	Upstream only	File metadata
`configuration_iquestpltcoder.py`	9.14 KB	—	Upstream only	File metadata
`generation_config.json`	216 bytes	`15c39458…f5396f5c` `15c394589d18595f78c759439184cbd7aae9e17e05e0ee45e295a69ff5396f5c`	Hosted	डाउनलोड करें
`model.safetensors.index.json`	14.2 KB	`3795db19…f4463d44` `3795db19eee7bf2c7662f5d1610880664f883f12c420cac16479be47f4463d44`	Hosted	डाउनलोड करें
`special_tokens_map.json`	861 bytes	`003fa5c9…85b1a1cf` `003fa5c9469dcd5f896f6ae1bf4a014f12f1e7eb31e6e8270099b86685b1a1cf`	Hosted	डाउनलोड करें
`tokenization_iquestcoder.py`	22.6 KB	—	Upstream only	File metadata
`tokenizer.json`	8.13 MB	`33cb3a4d…e5eb7385` `33cb3a4de4295114749bdc0fa9c6bb1bc2d4e91f9c311857ed8efb21e5eb7385`	Hosted	डाउनलोड करें
`tokenizer.model`	1.35 MB	`7d3be68e…c9c1cd91` `7d3be68e090a927f31e0e378d7599b15c206dd47e4a73933775a746cc9c1cd91`	Hosted	डाउनलोड करें
`tokenizer_config.json`	6.21 KB	`83257bfd…4de6b179` `83257bfd11c1ce0dc70a95847081999707f40f72a9efb80d1b53e27d4de6b179`	Hosted	डाउनलोड करें
Docs
`.gitattributes`	1.52 KB	—	Upstream only	File metadata
`README.md`	5.39 KB	`e301aa97…efe50a87` `e301aa970c2e248bd63f0733c881e4456322831ae439e4e66e23bb9defe50a87`	Hosted	डाउनलोड करें

डाउनलोड की जाँच करें

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.

मिलते-जुलते होस्ट किए गए मॉडल

होस्ट किए गए मॉडल देखें

LoopCoder-V2

डाउनलोड की जाँच करें

मिलते-जुलते होस्ट किए गए मॉडल

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