| --- |
| pretty_name: Deterministic Random Models |
| license: other |
| size_categories: |
| - n<1K |
| tags: |
| - llama |
| - gemma4 |
| - qwen3 |
| - smollm3 |
| - transformers |
| - safetensors |
| - gguf |
| - synthetic |
| - conformance |
| - compatibility-testing |
| --- |
| |
| # Deterministic Random Models |
|
|
| This dataset contains ten small, deterministic language-model fixtures for |
| model-format, loader, inference, compatibility, and conformance testing. They |
| are not trained models and must not be used for language-model quality |
| evaluation. |
|
|
| All weights are synthetic and deterministically generated. No original model |
| checkpoint weights are included. |
|
|
| ## Cases |
|
|
| | Case | Architecture | Parameters | Hugging Face | GGUF | Notable feature | |
| |---|---|---:|---|---|---| |
| | `tinyllama-chat` | Llama | 303,744 | F32 | Q4_K_M | GQA, query/KV ratio 8 | |
| | `smollm2-instruct` | Llama | 46,320 | F32 | Q4_K_M | GQA, query/KV ratio 3 | |
| | `mobilellama-chat` | Llama | 9,296 | F32 | Q4_K_M | MHA | |
| | `minicpm5` | Llama | 1,409,664 | F32 | Q4_K_M | explicit head dimension, multiple EOS IDs | |
| | `deepseek-coder` | Llama | 9,296 | F32 | Q4_K_M | linear RoPE scaling | |
| | `hermes3-llama31` | Llama | 86,336 | F32 | Q4_K_M | Llama 3 RoPE scaling | |
| | `livekit-turn-detector` | Llama | 132,336 | F32 | Q4_K_M | explicit head dimension, GQA | |
| | `gemma4-random-model` | Gemma 4 | 1,519,168 | BF16 | Q4_0 | five-local/one-global attention schedule | |
| | `qwen3-random-model` | Qwen 3 | 508,800 | BF16 | Q4_0 | wide Q projection and Q/K head norms | |
| | `smollm3-random-model` | SmolLM3 | 4,917,504 | BF16 | Q4_0 | three-RoPE/one-no-RoPE layer schedule | |
| |
| The seven Llama cases are derived from real Hugging Face configuration files by |
| a preservation-first shrinker. Gemma 4, Qwen 3, and SmolLM3 retain |
| architecture-specific reduced geometries that preserve important |
| ratios, tensor inventories, and layer schedules observed in locally downloaded |
| upstream GGUF models. Published case names use `random-model` rather than |
| `tiny-model` to avoid collision with a separately maintained TinyModel collection. |
| |
| ## Formats and layout |
| |
| The Llama cases retain the original dataset layout: |
| |
| ```text |
| <llama-case>/ |
| |-- package/model.safetensors # canonical F32 weights |
| |-- gguf/model-Q4_K_M.gguf |
| |-- tokenizer/ |
| |-- reference/outputs.safetensors |
| |-- inputs.safetensors |
| |-- case.json |
| |-- provenance.json |
| |-- source-config.json |
| |-- shrunk-config.json |
| |-- config-diff.json |
| `-- validation.json |
| ``` |
| |
| The architecture-specific cases use: |
| |
| ```text |
| <random-model-case>/ |
| |-- hf-bf16/ |
| | |-- config.json |
| | |-- model.safetensors |
| | |-- tokenizer.json |
| | `-- tokenizer_config.json |
| |-- gguf-q4_0/ |
| | |-- <case>-Q4_0.gguf |
| | `-- quantize.log |
| |-- reference/ |
| | |-- inputs.json |
| | |-- hf-outputs.safetensors |
| | `-- gguf-native.json |
| |-- CONFIG_DECISION.md |
| `-- metadata.json |
| ``` |
| |
| `manifest.json` is the machine-readable index of all ten model packages and |
| their SHA-256 hashes and sizes. |
| |
| ## Synthetic weights and tokenizers |
| |
| Weights use the `tlfloat::LCG64` recurrence with multiplier |
| `6364136223846793005`, increment `1442695040888963407`, and ten warm-up steps. |
| Each case records its seed and provenance. |
| |
| The reduced models use deterministic 128-token auxiliary vocabularies. These |
| tokenizers cover token IDs `0..127` and preserve each case's special-token |
| semantics, but they do not reproduce the linguistic behavior of the original |
| tokenizer. Explicit token IDs are the primary numerical-test interface. |
| |
| ## GGUF generation and validation |
| |
| GGUF files were generated with upstream `ggml-org/llama.cpp` commit |
| `40b740ad05c531b9d57aca6698c3ed553a9e784c`. |
| |
| Every retained GGUF was loaded through that revision and exercised with direct |
| token IDs for prefill, cached decode, logit extraction, finite-value checks, and |
| repeated-execution checks. The effective EOG token set was checked against the |
| model EOS semantics. Per-case metadata records the actual tensor-type histogram, |
| hashes, commands, and informational comparison with the corresponding |
| Transformers reference. |
| |
| Q4_K_M and Q4_0 are lossy formats. Their logits are not required to equal the |
| F32 or BF16 reference exactly. |
|
|
| ## Reproducibility and scope |
|
|
| The Hugging Face weights, configs, and GGUF outputs for Gemma 4, Qwen 3, and SmolLM3 were |
| independently regenerated and found byte-identical. The Llama cases retain their |
| source revisions, source-config hashes, shrink decisions, and generation |
| provenance in each case directory. |
|
|
| This dataset is not a pretrained-model collection, a model-quality benchmark, |
| or a reproduction of upstream weights or tokenizers. Source-derived configuration |
| and metadata files may remain subject to terms of their respective upstream |
| repositories; consult their recorded provenance before redistribution. |
|
|
| See `REPORT.md`, `GGUF_Q4_K_M_REPORT.json`, and |
| `ARCHITECTURE_RANDOM_MODELS_REPORT.json` for collection-level summaries. |
|
|
