gemma4-26b-biblical-qlora is an open-weight model from Serialhex. Its published files total 1.0 GB.
This model is a fine-tuned version of unsloth/gemma-4-26B-A4B-it. It has been trained using TRL. This model was trained with SFT.
Parameters—
Context—
Weights1.0 GB
License—
AccessOpen weights
Monthly Downloads—
Model Card
This model is a fine-tuned version of unsloth/gemma-4-26B-A4B-it. It has been trained using TRL. This model was trained with SFT.
Excerpt from the card by Serialhex.
Identity and Version
- Repository
- serialhex/gemma4-26b-biblical-qlora
- Publisher
- Serialhex
- Task
- Not stated by the source
- Modality
- Other
- Library
- transformers
- Parameters
- Not stated by the source
- Languages
- trl, sft
- Revision
- 56505c50c4b70e45b3b4a692850b1578ec15699a
- First published
- 2026-10-10
- Last updated
- 2026-10-11
Files and Weights
9 files, 1.0 GB in total. The weights are 2 files totalling 1.0 GB in bin, safetensors.
Weights2 files · 1.0 GB
Configuration2 files · 3.8 KB
Tokenizer2 files · 32.2 MB
Documentation1 file · 1.5 KB
Other1 file · 18.9 KB
Repository1 file · 1.6 KB
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| adapter_model.safetensors | Weights | 1.0 GB | 4ff3efc43fcb |
| training_args.bin | Weights | 5.9 KB | b04d5554d417 |
| adapter_config.json | Configuration | 2.2 KB | — |
| processor_config.json | Configuration | 1.7 KB | — |
| README.md | Documentation | 1.5 KB | — |
| chat_template.jinja | Other | 18.9 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| tokenizer.json | Tokenizer | 32.2 MB | cc8d3a0ce364 |
| tokenizer_config.json | Tokenizer | 2.7 KB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 1.0 GB
Download from Serialhex
Released by Serialhex through its official repository on Hugging Face.
Built From
- Derived from unsloth/gemma-4-26B-A4B-it
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 1.0 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.