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Gemma4-Gutenberg-12B-lora

nbeerbower/Gemma4-Gutenberg-12B-lora

fine-tuned
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About this model

nbeerbower's Gemma4-Gutenberg-12B-lora is a derivative of google/gemma-4-12B-it. According to the model card, it was trained with ORPO using LoRA adapters on the schneewolflabs/Alembic-DPO dataset, with the LoRA weights merged before upload. The card includes a Merlina training configuration for reproducing the run and lists 4-bit NF4 quantization during training. The repository is provided as safetensors weights, and no license is listed in the metadata.

Description sources

Source-based description, not an independent evaluation. Check the linked sources for the creator’s claims and limitations.

Size and formats

Base model
google/gemma-4-12B-it
Parameters
Unknown
Main repository formats
safetensors
License tag
Unknown
Languages
Unknown
Last updated
2026-07-05 · 16:57:30.000 UTC

What changed

Model types are creator-reported, not independently tested. These labels describe source metadata, not a guarantee of behavior.

  • fine-tunedsource tag: base_model:finetune:google/gemma-4-12B-it

Family evidence

These groupings are source-reported. Explicit base identifiers take priority over generic architecture tags.

  • Gemma: Base model: google/gemma-4-12B-it

Available versions

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Link to this listing

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Customize or build on this model

Listed from public GitHub data, not tested by us. Read the code and license before you run anything.

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Source provenance

Downloads
0
Likes
6
Metadata checked
2026-10-25 · 20:12:36 UTC
First seen in index
2026-10-25 · 20:12:36 UTC
Source revision
c877dab17e6a7e12ee85bf9ab11d38475ef8fbfb

Source-card excerpt

Source model card excerpt: Gemma4-Gutenberg-12B Training Configuration Parameter Value ----------- ------- Training Mode ORPO Base Model google/gemma-4-12B-it Learning Rate 5e-05 Epochs 1 Batch Size 1 Gradient Accumulation 32

From nbeerbower/Gemma4-Gutenberg-12B-lora. Creator model-card excerpt, not an independent review.

Inspect before you run

Low refusal is not proof of correctness. Outputs can be inaccurate, harmful, or biased. Review the model card, license and files yourself. A license tag is not commercial-use advice. Parameter counts are source metadata; no hardware compatibility is implied.

This directory does not host or redistribute model weights. Refusal profiles are measured by us on a fixed prompt set; all other behavior claims are source-reported.

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