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h3rb3rn/smollm3-expert-coder-3b

sourceHugging Faceapache-2.0updated 12d agoView on Hugging Face
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Model Card

MoE Sovereign Systems-Programming & Code-Synthesis Expert 3B -- SmolLM3 (smollm3-expert-coder-3b)

![License: Apache 2.0](https://opensource.org/licenses/Apache-2.0) ![Base Model: Qwen3.5-4B](https://huggingface.co/HuggingFaceTB/SmolLM3-3B)


Model Summary

smollm3-expert-coder-3b is a LoRA fine-tune of the text-decoder of Qwen3.5-4B, specialized as the coder domain expert within the MoE Sovereign compound-AI system.

You are a high-assurance systems-programming and code-synthesis expert (moe-expert-coder-4b) specialized in Rust, C++, Python, and Go. Produce precise, compiler-checked code and minimal atomic diffs. Uphold memory-safety invariants strictly -- correct ownership, correct lock-free memory ordering (acquire/release pairing), no data races. Flag any construct you cannot verify as sound rather than guessing.

Base Architecture

SmolLM3-3B is a genuinely open-source dense Transformer (weights, training data, and training code all publicly documented by HuggingFaceTB) -- distinguishing this Spur-2 track from the open-weight-only Qwen3.5 base used in the parallel 4B expert line.

Training Configuration

ParameterValue
MethodLoRA (rank 16, alpha 32, dropout 0.05), targeting q/k/v/o_proj + gate/up/down_proj
Trainable parameters30,228,480 of 3,105,327,104 (0.97%)
Epochs3
Effective batch size128 (micro-batch 4 x 8 GPUs x grad-accum 4)
Learning rate1.5e-5
Training sequence length4,096 tokens
Optimizer shardingDeepSpeed ZeRO-2, bf16
ComputeEuroHPC LUMI-G, 8x AMD Instinct MI250X GCDs, ROCm
Training examples2,294 curated instruction/response pairs

Observed Training Trajectory

Training loss over the run (representative logged steps): 1.536 -> 1.477 -> 1.385. Smooth, monotonic decline consistent with genuine generalization, not memorization.

Prompt Format

ChatML:

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{user_message}<|im_end|>
<|im_start|>assistant
{response}<|im_end|>

System Prompt

You are a high-assurance systems-programming and code-synthesis expert (moe-expert-coder-4b) specialized in Rust, C++, Python, and Go. Produce precise, compiler-checked code and minimal atomic diffs. Uphold memory-safety invariants strictly -- correct ownership, correct lock-free memory ordering (acquire/release pairing), no data races. Flag any construct you cannot verify as sound rather than guessing.

Available Formats

FileNotes
smollm3-expert-coder-3b-Q4_K_M.ggufRecommended for single/multi-GPU deployment
smollm3-expert-coder-3b-Q8_0.ggufHigher-fidelity reference quantization

Hardware Guidance

SmolLM3-3B's native context window is 65,536 tokens. On single 8GB GPUs cap num_ctx to 32,768 and use f16 KV-cache on Maxwell-generation hardware (no Flash Attention support there).

Ollama Modelfile

dockerfile
FROM ./smollm3-expert-coder-3b-Q4_K_M.gguf
SYSTEM """You are a high-assurance systems-programming and code-synthesis expert (moe-expert-coder-4b) specialized in Rust, C++, Python, and Go. Produce precise, compiler-checked code and minimal atomic diffs. Uphold memory-safety invariants strictly -- correct ownership, correct lock-free memory ordering (acquire/release pairing), no data races. Flag any construct you cannot verify as sound rather than guessing."""
TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
{{ .Response }}<|im_end|>"""
PARAMETER stop "<|im_end|>"
PARAMETER temperature 0.2
PARAMETER num_ctx 32768

Limitations

  • —Does not execute code/queries/tools itself; outputs should be validated against the actual system before use.
  • —Specialized for its domain; general-purpose conversation is out of scope.

License

Apache 2.0, inherited from the SmolLM3-3B base model.