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Gemma-4-12B-Sol-Traces-v1
RedTeamLab/Gemma-4-12B-Sol-Traces-v1
Gemma-4-12B-Sol-Traces-v1 is a machine learning model from RedTeamLab. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for gguf. The card lists the license as gemma.
Repository coding-agent model fine-tuned from unsloth/gemma-4-12B-it with LoRA on a verified original-synthetic corpus compiled from Hermes Agent session logs. The traces do not originate from OpenCode.
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At a glance
- Library
- gguf
- License
- gemma
- Access
- Public
- Created
- Jul 15, 2026
- Updated
- Jul 16, 2026
- SHA
- 9f11ceb4
Base models
Model card
From the Hugging Face model README
Gemma-4-12B-Sol-Traces-v1
Repository coding-agent model fine-tuned from unsloth/gemma-4-12B-it with LoRA on a verified original-synthetic corpus compiled from Hermes Agent session logs. The traces do not originate from OpenCode.
Verified training configuration
| Parameter | Value |
|---|---|
| Base model | unsloth/gemma-4-12B-it |
| Fine-tuning | LoRA, r=16; language + attention layers |
| Dataset | 25,000 accepted trajectories: 21,174 train / 1,324 validation / 2,502 test |
| Epochs | 1 |
| Learning rate | 1e-4, cosine schedule, 3% warmup |
| Effective batch size | 8 (2 × 4 gradient accumulation) |
| Maximum sequence length | 8,192 tokens |
| Loss | Assistant-only; tool responses excluded |
| GPU | Modal H100 80GB |
| Completed steps | 377 |
| Training loss | 0.080072 |
| Validation loss | 0.025797 |
| Runtime | 10,848 s (3h 00m 48s) |
| Peak VRAM | 46.72 GiB |
| Throughput | 1,138.7 tokens/s |
Dataset and trajectory policy
Sol Traces are compiled from Hermes Agent session logs produced while running deterministic, seed-based coding scenarios through a reference executor. The scenarios define repository templates, task requirements, and verification commands; accepted records retain the corresponding tool-use events and verification outcomes. Records are included only when their configured post-task validation succeeds.
Actual v1 coverage: 224 language/task/variant repository families across TypeScript, JavaScript, Python, shell, configuration, Go, Rust, and JVM/Java. Task categories are debugging, feature, refactoring, testing, build configuration, integration, and documentation review.
The schema defines list_files, read_file, search_code, run_command, and apply_patch. The v1 reference policy emits list_files, read_file, run_command, and apply_patch; it has no search_code calls. This model is therefore best understood as a fine-tune for the verified scripted v1 workflow, not a broadly trained autonomous coding agent.
Files
| File | Description |
|---|---|
gemma-4-12b-sol-traces-v1-Q4_K_M.gguf | Quantized merged model (Q4_K_M) |
gemma-4-12b-sol-traces-v1-f16.gguf | Full merged F16 model |
training_stats.json | Full training metrics |
training_report.json | Duplicate training report retained for compatibility |
dataset_manifest.json | Accepted-record counts, split ratios, and rejection summary |
Usage
llama-cli \
-m gemma-4-12b-sol-traces-v1-Q4_K_M.gguf \
-ngl 99 \
--chat-template gemma \
-p "List the repository files matching *.py"
Limitations
- Fixed five-tool schema;
search_codewas not used in v1 training trajectories. - Single-trajectory sessions; no training for memory across independent conversations.
- Synthetic repository fixtures and a deterministic reference policy may not generalize to arbitrary real-world codebases.
- Library
- gguf
- License
- gemma
- Languages
- en
- Created
- Jul 15, 2026
- Updated
- Jul 16, 2026