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LICENSE) for the original terms, including the
naming clause that accompanies the Apache-2.0 license.Qwen/Qwen3-0.6B (Qwen3ForCausalLM, 28 layers, GQA 16 Q heads / 8 KV heads, head_dim 128,
hidden_size 1024, vocab_size 151936, tied embeddings). It is not a general-purpose chat
model — it performs a single task: cleaning up raw, lowercase, unpunctuated ASR
transcripts into normalized text according to a control line.You are a text normalizer for speech-to-text transcripts. The input begins with a control line specifying the styling, structure, and context settings; clean the transcript to match those settings and output only the cleaned text.1[Styling: semi-formal] [Structure: prose] [Context: general]
2<raw lowercase unpunctuated asr transcript>Styling: semi-formal|formal|casual,
Structure: prose|lists, Context: general|email|.... The model outputs only the
cleaned transcript — no explanation, no preamble.enable_thinking=False and greedy decoding (do_sample=False, temperature=0,
max_new_tokens=1024). Sampling is not validated for this model and may degrade output
quality/consistency.Note onenable_thinking=False: the model's chat template signals this by emitting an empty `
block immediately after the<|im_start|>assistant
`header. If you build prompts manually instead of through the chat template, include that block explicitly.
Note ontemperature: withdo_sample=False, omit/avoid settingtemperature=0.0explicitly in onnxruntime-genai'sGeneratorParams.set_search_options— some onnxruntime-genai builds divide logits bytemperatureeven in greedy mode, which crashes on a literal0.0. Leavetemperatureunset for greedy decoding.
onnxruntime-genai 0.15.1. Running the fp16/ variant fails with a shape-mismatch error inside the
ONNX Runtime buffer-reuse optimizer, in the GQA repeat_kv Reshape node
(InsertedPrecisionFreeCast_/model/layers.*/attn/v_proj/repeat_kv/Reshape_4).
Use the int4/ variant for CPU inference until this is confirmed fixed in a
newer onnxruntime-genai release. The fp16/ artifact is still published here for
future compatibility/GPU experimentation, but it is not currently validated to run.tokenizer.decode() on an empty token sequence (which can legitimately
happen — e.g. pure-filler input that should normalize to nothing) crashes the
native onnxruntime-genai decoder with an integer divide-by-zero. Guard for a
zero-length generated sequence in calling code and treat it as an empty string
instead of calling decode().| Field | Value |
|---|---|
| Source | superwhisper/s1-mini |
| Precision | INT4 |
| Execution provider | CPU (universal) |
| Tool | onnxruntime_genai.models.builder |
| Architecture | Qwen3-0.6B decoder-only |
1using var client = await LocalChatClient.CreateAsync(new LocalLLMsOptions
2{
3 Model = KnownModels.S1Mini,
4 EnsureModelDownloaded = true // downloads automatically on first run
5});
6
7var response = await client.CompleteAsync(
8 "[Styling: semi-formal] [Structure: prose] [Context: general]\n" +
9 "so um i need to like send the the report by uh friday no wait make that thursday");LICENSE file or
https://huggingface.co/superwhisper/s1-mini/raw/main/LICENSE for the authoritative text.