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RedTeamLab/Gemma-4-E4B-Sol-Traces-v4
Gemma-4-E4B-Sol-Traces-v4 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.
Targeted routing-repair continuation from v3. Continuation-trained on 125 mined trajectories (SWE-bench, synthetic, bash history, GitHub commits) to fix runcommand, searchcode, and applypatch tool selection.
Downloads · 30 days
104
40% of all-time downloads
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.gguf20.4 GB · 100%
From the Hugging Face model README
Targeted routing-repair continuation from v3. Continuation-trained on 125 mined trajectories (SWE-bench, synthetic, bash history, GitHub commits) to fix run_command, search_code, and apply_patch tool selection.
| Parameter | Value |
|---|---|
| Base model | unsloth/gemma-4-E4B-it |
| Adapter start | v3 from-scratch (336 LoRA keys) |
| Training type | Continuation (100 steps) |
| Dataset | 125 train / 15 val / 17 test |
| Sources | SWE-bench (50), synthetic (50), bash history (55), GitHub (2) |
| Tool schema | 6 tools (search_code, run_command, apply_patch, read_file, list_files, write_file) |
| Learning rate | 3e-5, cosine, 3% warmup |
| Batch | 1 × 8 grad accum |
| Runtime | 12 min on H100 |
| Training loss | 0.093 |
| Eval loss | 0.671 |
| Cost | ~$0.80 |
| Tool | v1 | v2 | v3 | v4 |
|---|---|---|---|---|
| run_command | 2/5 | 0/5 | 0/5 | 5/5 ✅ |
| search_code | 0/5 | 0/5 | 0/5 | 1/5 |
| apply_patch | 1/5 | 0/5 | 0/5 | 0/5 |
| list_files | 5/5 | 5/5 | 5/5 | 4/5 |
| read_file | 4/5 | 5/5 | 5/5 | 5/5 |
| no-tool | 4/5 | 5/5 | 5/5 | 3/5 |
| Overall | 53% | 50% | 50% | 60% |
| File | Size |
|---|---|
gemma-4-e4b-sol-traces-v4-Q4_K_M.gguf | 4.97 GiB |
gemma-4-e4b-sol-traces-v4-f16.gguf | 14.02 GiB |
adapter/adapter_model.safetensors | 35 MiB |
training_stats.json | — |
llama-cli -m gemma-4-e4b-sol-traces-v4-Q4_K_M.gguf -ngl 99