TIPO-500M-GGUF GGUF download (314 MB) | Hugging Bay

TIPO-500M-GGUF

QuantFactory/TIPO-500M-GGUF

Model details

text generationLicense: unknownSHA-256 recorded for 14 of 16 filesGGUF

Content controls: not assessed.

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

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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-quantfactory-tipo-500m-gguf/TIPO-500M.Q4_K_M.gguf",
    "TIPO-500M.Q4_K_M.gguf",
)

Other ways

Run it on your computerOpen in Hugging Bay appSend to a computerMac (Apple silicon) and Linux x86_64 installs are listed on the download page. Windows and Intel Mac are not yet. The app checks this model before you choose to download.

1 hosted of 16 listed · Hashes recorded. Date not recorded.

Selected downloadTIPO-500M.Q4_K_M.gguf314 MB · 1 file Download · 314 MB (1 file)

Open-file help

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

Model facts

TIPO-500M-GGUF is an open-weights language model for text generation. The primary file is TIPO-500M.Q4_K_M.gguf (314 MB, Q4_K_M). The primary file needs about 2 GB free for the Q4 file (file plus room to run it). License: unknown. The SHA-256 prefix is ed349456222a. The primary Download is available now. No tested run commands for this file yet. The license label is unknown; availability is shown separately. The size and hash details refer to the selected file, not every file in the repository. The memory figure is estimated from recorded file size with working room included.

What's included

1 hosted of 16 listed

Weights

README, LICENSE & .gitattributes

About this model

External Hugging Face catalog record for QuantFactory/TIPO-500M-GGUF. Task: text generation. Library: transformers. Languages: en. Datasets referenced by card metadata: laion/conceptual-captions-12m-webdataset, CaptionEmporium/coyo-hd-11m-llavanext, KBlueLeaf/danbooru2023-metadata-database, graph-based-captions/GBC10M. Popularity signal at import: 916 downloads and 4 likes.

Quick facts

Parameters: 500M
Hosted here: 1 hosted of 16 listed
Full repo upstream: 4.63 GB
Recommended file: 314.1 MB (Q4_K_M) · TIPO-500M.Q4_K_M.gguf
Languages: en
Format: GGUF
Downloads on Hugging Face: 916
File hashes: Hashes recorded. Date not recorded.

License & source

License: unknown

1 hosted of 16 listed

No license was found in metadata, the LICENSE file or README. You can download the files; check the terms before you use or share them.

See the JSON record →

License: unknown
Task: text generation
Hosted here: 1 file, 314.1 MB
Full repo upstream: 4.63 GB
Recommended file: 314.1 MB (Q4_K_M) · TIPO-500M.Q4_K_M.gguf
Parameters: 500M
Files: 1 hosted of 16 listed
Download: Download here (1 hosted file)
Added to Hugging Bay: Sep 19, 2026
Updated at source: Sep 19, 2026
Source: QuantFactory/TIPO-500M-GGUF

FAQ

What is this model?

QuantFactory/TIPO-500M-GGUF is an open-weights language model for text generation published by QuantFactory, added to Hugging Bay Sep 19, 2026. Model from Hugging Face for text generation: QuantFactory/TIPO-500M-GGUF · transformers

Can I use it commercially?

License: unknown. Check the upstream license text or ask the model author before commercial use.

How big is it?

QuantFactory/TIPO-500M-GGUF has 500M parameters. Hosted here: 1 file, 314.1 MB. Full repo upstream: 4.63 GB. The recommended download, TIPO-500M.Q4_K_M.gguf (Q4_K_M), is 314.1 MB.

What can I download here?

Hosted here: 1 file, 314.1 MB. Full repo upstream: 4.63 GB.

File checks and computer fit

File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 1 hosted file carries a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-quantfactory-tipo-500m-gguf/safety on Hugging Bay.

Will QuantFactory/TIPO-500M-GGUF 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.