| ---
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| license: other
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| license_name: stream-1-mini-license
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| license_link: LICENSE
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| language:
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| - en
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| base_model: Qwen/Qwen3-0.6B-Base
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| base_model_relation: finetune
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| pipeline_tag: text-generation
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| tags:
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| - qwen3
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| - dictation
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| - text-normalization
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| - text-generation
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| - gguf
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| ---
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|
|
| # Stream-1 Mini by Whisperstream
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|
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| Stream-1 Mini turns English dictation transcripts into clean Chat and Email
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| text on your own device. It is trained to remove fillers and accidental repeats,
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| add punctuation, and resolve spoken corrections while preserving your meaning
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| and voice. Email mode also formats dictated greetings, paragraphs and sign-offs.
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|
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| This revision adds optional custom-vocabulary hints while retaining structural
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| dictation and numbered-list support. Use these prompts and weights together.
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| Candidates are spelling hints, not forced substitutions. Known cleanup and entity
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| errors remain; this revision does not establish zero regressions.
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|
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| Pass in text from your speech recognizer. Stream-1 Mini returns the cleaned text.
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|
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| | Specification | Value |
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| | --- | --- |
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| | Task | English dictation cleanup |
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| | Modes | Chat and Email |
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| | Base model | [Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base/tree/da87bfb608c14b7cf20ba1ce41287e8de496c0cd) |
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| | Parameters | 751,632,384, with separate input embeddings and output weights |
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| | Formats | Full-precision FP32 Safetensors, F16 GGUF and Q4_K_M GGUF |
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| | GGUF download | 484,215,648 bytes (about 484 MB) |
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| | Tested context | 4,096 tokens, with up to 512 output tokens |
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| | License | [Stream-1 Mini License](LICENSE), permitting commercial use with attribution |
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|
|
| ## Structural dictation
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|
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| The intended behavior is to convert in-place commands while preserving literal
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| content. These examples describe the policy, not additional measured tests:
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|
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| | Dictation cue | Intended output |
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| | --- | --- |
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| | new line | One line break |
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| | new paragraph | A blank line |
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| | exclamation mark / exclamation point | `!` |
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| | Packing list. Bullet point socks. Bullet point charger. | A lead-in followed by two bullet items |
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| | First, passport. Second, charger. Third, jacket. | Three numbered items |
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|
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| Keep phrases such as "a new line of products" and "Please turn the report into
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| bullet points" as dictated text. Spoken period, full stop, comma and question
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| mark conversion is outside this release's structural-command scope.
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|
|
| ## Quickstart
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|
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| Use Python 3, the
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| [Hugging Face CLI](https://huggingface.co/docs/huggingface_hub/guides/cli) (`hf`), and
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| [llama.cpp b10537](https://github.com/ggml-org/llama.cpp/releases/tag/b10537).
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| Download the model and its prompts into a local folder:
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|
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| ```shell
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| hf download whisperstream/stream-1-mini stream-1-mini-vocabulary-q4_k_m.gguf prompts.json chat_template.jinja vocabulary_contract.py --local-dir stream-1-mini
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| ```
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| Start the CPU server. On Windows, the executable may be named `llama-server.exe`.
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|
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| ```shell
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| llama-server -m stream-1-mini/stream-1-mini-vocabulary-q4_k_m.gguf --host 127.0.0.1 --port 8080 -c 4096 -b 256 -t 6 -np 1 -ngl 0 --chat-template-file stream-1-mini/chat_template.jinja
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| ```
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| Save this as `clean.py` beside the `stream-1-mini` folder. It sends one dictation
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| to the local server:
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|
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| ```python
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| import json
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| import sys
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| from pathlib import Path
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| from urllib.request import Request, urlopen
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|
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| prompts = json.loads(Path("stream-1-mini/prompts.json").read_text(encoding="utf-8"))
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| sys.path.insert(0, str(Path("stream-1-mini").resolve()))
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| from vocabulary_contract import render_messages
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| vocabulary = [] # Optional relevant dictionary spellings, not the entire dictionary.
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| mode = "chat" # Use "email" for Email mode.
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| transcript = "um let's meet on tuesday no wednesday at three pm"
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|
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| payload = {
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| "messages": render_messages(prompts[mode], transcript, vocabulary),
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| "temperature": 0,
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| "top_k": 1,
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| "top_p": 1,
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| "repeat_penalty": 1,
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| "max_tokens": 512,
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| "cache_prompt": True,
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| "chat_template_kwargs": {"enable_thinking": False},
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| }
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| request = Request(
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| "http://127.0.0.1:8080/v1/chat/completions",
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| data=json.dumps(payload).encode("utf-8"),
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| headers={"Content-Type": "application/json"},
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| )
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| with urlopen(request, timeout=120) as response:
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| choice = json.load(response)["choices"][0]
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| if choice["finish_reason"] != "stop":
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| raise RuntimeError("Cleanup did not finish. Keep the original transcript.")
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| print(choice["message"]["content"])
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| ```
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|
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| In another terminal, run `python clean.py` from that same folder. Change `mode`
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| to `"email"` and replace `transcript` to try Email mode. Keep each request limited
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| to its current transcript.
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|
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| ## Files
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|
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| The full-precision distribution contains four FP32 Safetensors shards, their
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| index, tokenizer, configuration and chat template. It supports further
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| modification without starting from quantized weights. Those full-precision
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| weights are the retained source of the GGUF conversion; the evaluation below
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| applies specifically to Q4_K_M with the stated serving setup.
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|
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| `stream-1-mini-f16.gguf` provides the 16-bit GGUF export for llama.cpp-compatible
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| runtimes. It contains 1,509,343,072 bytes (about 1.51 GB).
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|
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| `stream-1-mini-vocabulary-q4_k_m.gguf` is the selected inference artifact. It contains
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| 484,215,648 bytes; SHA256:
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|
|
| ```text
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| 32bef61bdbc98787ac278d96a2aad120a9fc61f588f1f0a4746441e9d6d89ae7
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| ```
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|
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| `prompts.json` contains the exact Chat and Email system prompts. Keep these
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| prompts and the supplied template together with the model. See `LICENSE`,
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| `LICENSE-APACHE-2.0`, and `NOTICE` for terms and attribution.
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|
|
| ## Integration notes
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|
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| > [!IMPORTANT]
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| > Use the chosen mode's system prompt and one user message containing only the
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| > current transcript, enclosed by `<TRANSCRIPT>` and `</TRANSCRIPT>`. An optional
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| > JSON `<VOCABULARY>` block follows it; append the canonical spelling exception
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| > to the system prompt only when the block is nonempty. The supplied
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| > `vocabulary_contract.py` renders this exact contract (32 terms, 512 UTF-8 bytes). Render with
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| > the supplied plain ChatML template, add the assistant generation prefix and
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| > do not inject a thinking preamble or conversation history.
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|
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| The full regression collection used llama.cpp b10537 on Vulkan. CPU app smoke
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| checks are separate runtime evidence. Use the evaluated greedy contract with
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| 4,096-token context, batch size 256, one slot and one request at a time.
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| Decode greedily: temperature 0, top-k 1, top-p 1, repeat penalty 1, and at most
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| 512 output tokens. Stop at the end-of-turn token. The training/export stop IDs
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| are 151643 and 151645; the GGUF end-of-turn ID is 151645.
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|
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| Enable prefix caching and keep Chat and Email sessions separate. Reuse a prompt
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| prefix without adding earlier dictations to the current request. Reject
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| incomplete or invalid generations and retain the original transcript when
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| cleanup fails. Users should be able to inspect and recover the original text.
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|
|
| ## Training and evaluation
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|
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| This revision continues the published v2 model with a balanced cleanup,
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| structural/list and vocabulary mixture. The selected terminal checkpoint used
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| training seed 23 and 648 optimizer updates. Training data and internal transcripts
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| are not distributed. FP32 and F16 files retain the conversion source; evaluation
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| applies specifically to Q4_K_M with the fixed prompts, decoder and cache contract.
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|
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| The selected candidate completed 3,409 registered requests, including all 1,600
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| historical C/D/E cleanup memberships, structure/list tests, vocabulary tests,
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| preservation controls and actual production chunk requests. These are observed
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| benchmark cases, with repeated memberships; they are not independent production
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| events or untouched confirmation.
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|
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| Provisional delivered cleanup counts across those 1,600 memberships are 1,216
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| pass, 12 warning, 202 hard failure, 53 critical failure and 117 unresolved.
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| Unresolved judgments are not passes. Later focused feature review retained
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| substantial vocabulary gains as well as failures:
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|
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| | Fresh positive-repair condition / 60 | Previous v2 pass / unresolved | This revision pass / unresolved |
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| | --- | ---: | ---: |
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| | Supplied vocabulary | 7 / 1 | 31 / 11 |
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| | Retrieved vocabulary | 13 / 2 | 30 / 9 |
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|
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| These purposively difficult cases do not estimate production recovery rates.
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| Feature success requires the whole output, not just inclusion of a target name.
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| Supplied-list negative controls can worsen even where vocabulary repair improves.
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| Known critical regressions include deleting an independent reported account and
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| substituting a distractor entity for a protected ordinary phrase.
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|
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| Twenty separate observed-case CPU app calls completed without transport failures,
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| timeouts or output caps. On the measured host, median request time was 0.97 s,
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| maximum 2.54 s and peak server working set about 0.96 GiB. These are runtime smoke
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| measurements, not quality qualification, whole-app RAM or microphone-to-insertion
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| latency. Three of six paired repeats differed byte-for-byte; one repeat reversed
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| an explicit host correction. Greedy settings and prefix reuse do not guarantee
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| identical outputs across cache histories.
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|
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| Fresh untouched confirmation was waived for this publication. Remaining critical
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| errors and unresolved judgments are disclosed, not rescored as passes. No claim
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| of general non-regression, CPU/GPU equivalence or dependable laptop tail latency
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| is made. Verify consequential names, numbers, conditions and corrections.
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|
|
| ## Limitations
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|
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| > [!WARNING]
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| > The model can change meaning, retain an incorrect number after a correction,
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| > or infer the wrong numeric scale. Review names, numbers, restrictions and
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| > other consequential details before relying on cleaned text.
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|
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| This release has not established support for code, arbitrary style controls,
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| multilingual cleanup or general question answering. Instructions within a
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| transcript should remain dictated content, except the supported in-place
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| structural dictation cues described above. The model has not been validated
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| for medical, legal or other high-stakes decisions. Smaller quantizations and
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| changed prompts may behave differently.
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|
|
| ## License
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|
|
| > [!IMPORTANT]
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| > Personal and commercial use, modification and redistribution are permitted
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| > under the [Stream-1 Mini License](LICENSE), which combines Apache-2.0 terms
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| > with an identification requirement for **Stream-1 Mini by Whisperstream**.
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| > This is a custom license, not unmodified Apache-2.0. See the license for
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| > permitted attribution locations and treatment of modified versions.
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| |
