TheOneWhoWill

Coding-Monkey-Gemma-GGUF

Code

Coding-Monkey-Gemma-GGUF is an open-weights language model for text generation from TheOneWhoWill, published on Hugging Face as TheOneWhoWill/Coding-Monkey-Gemma-GGUF. The recommended 7.4 GB Q4_K_M file fits comfortably in 24 GB of memory and needs at least 16 GB (a file size estimate, not a tested run). Hugging Bay hosts 1 file for this model. License: Apache 2.0.

What we checked

File: check availability in Files.

Memory: Fit unknown. File size needed to check fit.

Last recorded run: none for this selected file.

License BFiles CRuns F

Recorded checks do not guarantee safety or performance on your computer.

See file checks and sources
Model details
Chat & writeLicense label: apache-2.0SHA-256 recorded for 5 of 7 filesGGUF
Quick answer: compatibility and sources

Can I run Coding-Monkey-Gemma-GGUF on my computer?

It depends on your memory, processor, file format and runtime. A download is not confirmed by the current file evidence; inspect the file record before trying it. A file-size fit is an estimate, not a successful run or speed promise. Read the license before use.

Coding-Monkey-Gemma-GGUF is an open-weights language model for text generation. Model weights are learned parameters; a runtime loads them. A hosted file is an individual file Hugging Bay can serve. SHA-256 identifies exact file bytes. The availability date above applies to this file record, not the upstream metadata update date.

As of the recorded file availability check on .

Recorded SHA-256 for gemma-coder-Q4_K_M.gguf: f6ed4f8a9c851cd8b96832fb4831fe790f0c9580665bf0ca5833d151bfeb9057. Exact file evidence · Machine-readable source facts · Run evidence and any recorded receipts. A checksum fingerprints only the named file bytes; it does not prove safety, quality, a complete multi-file selection or a successful run.

Page text updated .

Model metadata: As of at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked .

Key facts

Catalog record
Summarizes upstream metadata; it is not itself a download or run receipt.
File evidence
Lists exact filenames, availability and any recorded SHA-256 for individual files.
Run evidence
Reports measured results only when a receipt exists for named file bytes and a setup; otherwise unmeasured.
Checksum scope
SHA-256 fingerprints one file’s bytes; it does not prove safety, quality or a multi-file bundle.

Evidence you can inspect (plain text)

  • This page’s quick answer names the file record for hf-model-theonewhowill-coding-monkey-gemma-gguf.
  • Open /artifact/hf-model-theonewhowill-coding-monkey-gemma-gguf/files for exact filenames, availability and any recorded SHA-256 for this model.
  • Open /evidence/artifacts/hf-model-theonewhowill-coding-monkey-gemma-gguf for run-readiness evidence tied to that record; absent receipts stay unmeasured.
  • Open /api/artifacts/hf-model-theonewhowill-coding-monkey-gemma-gguf/card.md for machine-readable source facts (not a runtime test).
  • A matching checksum on this page fingerprints only the named bytes shown in file evidence.

Unmeasured states are stated explicitly; this page does not invent run scores or compatibility guarantees.

Which date applies to which fact

  • File availability check:
  • Committed page-copy sources:
  • Upstream model metadata: Dates on artifact records when shown; not implied by page-copy revision
  • Run receipts: Only on /evidence pages when recorded; otherwise unmeasured

Page-copy revision (Updated line above) identifies committed text sources, not upstream model edits or test outcomes.

Requirements and source record

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

TheOneWhoWill/Coding-Monkey-Gemma-GGUF

Content controls: not assessed.

The catalog lists this model as an add-on for generating code. Catalog sources: license label, model card license, base model, publisher tags, task label, model card task.

Recorded model facts

Repository
TheOneWhoWill/Coding-Monkey-Gemma-GGUF
Task
text-generation
License
apache-2.0
Framework
peft

7 files, 62.2 GB in total.

格式
GGUF

Fit and run

Fit We can't estimate memory for this model yet.

Check fit
Where this number comes from
  • gemma-coder-Q4_K_M.gguf~10 GB estimated RAM
  • gemma-coder-Q5_K_M.gguf~12 GB estimated RAM
  • gemma-coder-Q6_K.gguf~13 GB estimated RAM
  • gemma-coder-Q8_0.gguf~17 GB estimated RAM
  • gemma-coder-fp16.gguf~31 GB estimated RAM

Disk space on this computer is not measured.

File size multiplied by 1.3 provides an estimate of memory needed. Runtime, context length and other apps may need more. This is not a tested run.

Use another tool

Download a compatible GGUF file first. Tool and model compatibility vary.

  • Ollama: write a Modelfile with FROM pointing to the GGUF, then run ollama create my-model -f Modelfile and ollama run my-model.
  • llama.cpp: install llama.cpp and load the GGUF with llama-cli -m followed by its file path; use the model’s chat template if available.
  • LM Studio: import the GGUF from the downloaded file and load it in the app.

See run guidance

文件

gemma-coder-Q4_K_M.gguf

SHA-256 recorded

7.38 GBView file
gemma-coder-Q5_K_M.gguf

SHA-256 recorded

8.55 GBView file
gemma-coder-Q6_K.gguf

SHA-256 recorded

9.79 GBView file
gemma-coder-Q8_0.gguf

SHA-256 recorded

12.67 GBView file
gemma-coder-fp16.gguf

SHA-256 recorded

23.83 GBView file
All files and download checks →
Where this information comes from

包含内容

Download availability is being checked.

Weights
README, LICENSE & .gitattributes

关于此模型

External Hugging Face catalog record for TheOneWhoWill/Coding-Monkey-Gemma-GGUF. Task: text generation. Library: peft. Base model: TheOneWhoWill/Coding-Monkey-Gemma. Popularity signal at import: 5,510 downloads and 18 likes.

基本信息

Hosted here
Download availability is being checked.
Full repo upstream
62.2 GB
Recommended file
7.38 GB (Q4_K_M) · gemma-coder-Q4_K_M.gguf
Format
GGUF
File hashes
Hashes recorded. Date not recorded.

许可证与来源

License: apache-2.0

Check the license text and keep the required notices when you use or share the files.

Upstream source →

See the JSON record →

Task
text generation
Hosted here
1 file, 7.38 GB
Full repo upstream
62.2 GB
Recommended file
7.38 GB (Q4_K_M) · gemma-coder-Q4_K_M.gguf
Files
1 hosted of 7 listed
Added to Hugging Bay
Updated at source

FAQ

What is this model?

TheOneWhoWill/Coding-Monkey-Gemma-GGUF is an open-weights language model for text generation published by TheOneWhoWill, added to Hugging Bay Sep 16, 2026. Model from Hugging Face for text generation: TheOneWhoWill/Coding-Monkey-Gemma-GGUF · peft

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.

How big is it?

Hosted here: 1 file, 7.38 GB. Full repo upstream: 62.2 GB. The recommended download, gemma-coder-Q4_K_M.gguf (Q4_K_M), is 7.38 GB.

What can I download here?

Hosted here: 1 file, 7.38 GB. Full repo upstream: 62.2 GB. The original release is at https://huggingface.co/TheOneWhoWill/Coding-Monkey-Gemma-GGUF.

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-theonewhowill-coding-monkey-gemma-gguf/safety on Hugging Bay.

Will TheOneWhoWill/Coding-Monkey-Gemma-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.

TheOneWhoWill/Coding-Monkey-Gemma-GGUFView as JSON →

Content controls: not assessed.

Repack of theonewhowill/coding-monkey-gemma (from the publisher card on Hugging Face). This does not mean the files match the original weights.

Device fit from run reports

No device run reports recorded yet. Device fit has not been measured.

Run report details

Results describe the reported file and hardware, not a guarantee for your machine. Community reports have not been independently checked.

Run reports as JSON