nbeerbower / Model details
Gemma4-Gutenberg-26B-A4B-lora
nbeerbower/Gemma4-Gutenberg-26B-A4B-lora
About this model
nbeerbower's LoRA adapter for the instruction-tuned google/gemma-4-26B-A4B-it model, released as safetensors weights. The creator says it was trained for one epoch using ORPO on the Alembic-DPO dataset with 4-bit NF4 quantization and a LoRA rank of 64 targeting the first 30 transformer layers. The supplied configuration sets max_sequence_length to 1536, which is a configuration value rather than verified usable context. No license is specified in the repository 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-4-26B-A4B-it
- Parameters
- Unknown
- Main repository formats
- safetensors
- License tag
- Unknown
- Languages
- Unknown
- Last updated
- 2026-07-04 · 02:09:25.000 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-4-26B-A4B-it
Family evidence
These groupings are source-reported. Explicit base identifiers take priority over generic architecture tags.
- Gemma: Base model: google/gemma-4-26B-A4B-it
Available versions
Versions appear here only when they explicitly name this exact model as their source. Check each repository for available files.
- Main repository files ↗safetensors
- No other explicitly linked versions recorded.
Link to this listing
Made or quantized this model? Paste one of these into your model card or README so people can find this listing.
Markdown
[Listed on Custom Clankers](https://customclankers.com/models/nbeerbower-gemma4-gutenberg-26b-a4b-lora/)HTML
<a href="https://customclankers.com/models/nbeerbower-gemma4-gutenberg-26b-a4b-lora/">Listed on Custom Clankers</a>Plain text links only: no image, no script, nothing loaded from this site.
Customize or build on this model
Listed from public GitHub data, not tested by us. Read the code and license before you run anything.
Tools to customize it further
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Fine-tune it on your own data
- Unsloth ↗ ★ 78,549
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Make a smaller download (quantize)
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- MLX LM ↗ ★ 7,470
Apple's MLX package for running and fine-tuning models on Apple silicon. It can quantize models and upload them to the Hugging Face Hub, and supports LoRA and full fine-tuning.
Merge it with another model
- mergekit ↗ ★ 7,415
Merges pretrained models with many merge methods. It works out-of-core, so merges can run on a CPU or with as little as 8 GB of VRAM, and it also handles LoRA extraction and mixture-of-experts merges.
Learn the techniques
- LLM Course ↗ ★ 84,684
A free course with roadmaps and Colab notebooks. Its notebooks include one-click tools for merging with MergeKit, quantizing to GGUF, GPTQ, EXL2, AWQ and HQQ, and automatic abliteration with custom datasets.
Source provenance
- Downloads
- 0
- Likes
- 7
- Metadata checked
- 2026-10-25 · 20:12:36 UTC
- First seen in index
- 2026-10-25 · 20:12:36 UTC
- Source revision
- b1e577928df35a5713adf1423c307d3c7264191b
Source-card excerpt
Source model card excerpt: Gemma4-Gutenberg-26B-A4B Training Configuration Parameter Value ----------- ------- Training Mode ORPO Base Model google/gemma-4-26B-A4B-it Learning Rate 5e-05 Epochs 1 Batch Size 1 Gradient Accumulation 32
From nbeerbower/Gemma4-Gutenberg-26B-A4B-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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