Text Generation
Transformers
Safetensors
English
qwen3
asr
automatic-speech-recognition
text-normalization
inverse-text-normalization
punctuation
truecasing
speech-to-text
dictation
post-processing
conversational
text-generation-inference
Instructions to use superwhisper/s1-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use superwhisper/s1-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="superwhisper/s1-mini") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("superwhisper/s1-mini") model = AutoModelForCausalLM.from_pretrained("superwhisper/s1-mini", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use superwhisper/s1-mini with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "superwhisper/s1-mini" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "superwhisper/s1-mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/superwhisper/s1-mini
- SGLang
How to use superwhisper/s1-mini with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "superwhisper/s1-mini" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "superwhisper/s1-mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "superwhisper/s1-mini" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "superwhisper/s1-mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use superwhisper/s1-mini with Docker Model Runner:
docker model run hf.co/superwhisper/s1-mini
Softmaximalist commited on
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LICENSE
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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------------------------------------------------------------------------
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ADDITIONAL TERM
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In addition to the terms of the Apache License, Version 2.0 above: any
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use, distribution, or integration of this model, whether unmodified or
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as part of a derivative work or product, must continue to identify it
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by its original name, "S1-mini" by "Superwhisper", using that exact
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capitalization, regardless of any other name under which the model or
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a product incorporating it is marketed or distributed.
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README.md
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---
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license:
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base_model: Qwen/Qwen3-0.6B
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base_model_relation: finetune
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library_name: transformers
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- qwen3
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---
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#
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<div align="center">
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<img src="./banner.jpg" alt="
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[](https://superwhisper.com)
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[](https://discord.gg/tF98XvJNvB)
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On a held-out set of 6,183 English cases it reaches 94.4% token accuracy, and
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the quantized build is a 462 MB file that runs comfortably on a laptop CPU.
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This is release v1, and it covers English only.
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and will not follow general instructions; it does one job, and you steer it
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with a control line at the top of the input.
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## Set `enable_thinking=False`
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The chat template comes from Qwen3 unchanged, and Qwen3 turns on thinking mode
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by default.
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in its training data.
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> [!WARNING]
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and adversarial inputs: 94.4% token accuracy, measured greedy on the Q4_K_M
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GGUF build. The BF16 weights here should do at least as well.
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## Using
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be embedded in open-source and commercial software alike: dictation apps,
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meeting-notes tools, live captioning, voice-driven editors, or any pipeline
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that has to turn raw ASR output into text a person will read.
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It is a post-processing stage rather than a standalone system:
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```
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audio ──▶ ASR (Whisper, Parakeet, …) ──▶
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```
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The ASR's raw transcript becomes the transcript line, your app's settings
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[GGUF builds](https://huggingface.co/superwhisper/s1-mini-GGUF) exist for
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exactly that.
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Nothing about the model is
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in any integration are the input format documented above and the thinking
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flag; nearly every integration bug traces back to one of those.
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> Read the [LICENSE](LICENSE) before you ship. Apache 2.0 is permissive but
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> not obligation-free: you must retain the license text and attribution
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> notices, and state significant changes if you redistribute a modified
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> version.
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>
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>
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## License
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## Citation
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```bibtex
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@misc{s1mini2026,
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title = {
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author = {
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year = {2026},
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url = {https://huggingface.co/superwhisper/s1-mini}
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}
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---
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license: other
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license_name: s1-mini-license
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license_link: LICENSE
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base_model: Qwen/Qwen3-0.6B
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base_model_relation: finetune
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library_name: transformers
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- qwen3
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---
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# S1-mini by [Superwhisper](https://superwhisper.com)
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<div align="center">
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<img src="./banner.jpg" alt="S1-mini banner" width="100%">
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[](https://superwhisper.com)
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[](https://discord.gg/tF98XvJNvB)
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On a held-out set of 6,183 English cases it reaches 94.4% token accuracy, and
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the quantized build is a 462 MB file that runs comfortably on a laptop CPU.
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+
This is release v1, and it covers English only. S1-mini is not a chat model
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and will not follow general instructions; it does one job, and you steer it
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with a control line at the top of the input.
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## Set `enable_thinking=False`
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The chat template comes from Qwen3 unchanged, and Qwen3 turns on thinking mode
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by default. S1-mini was trained with thinking off and has no reasoning traces
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in its training data.
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> [!WARNING]
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and adversarial inputs: 94.4% token accuracy, measured greedy on the Q4_K_M
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GGUF build. The BF16 weights here should do at least as well.
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## Using S1-mini in your own app
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S1-mini is Apache 2.0, the same license it inherits from Qwen3-0.6B, so it can
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be embedded in open-source and commercial software alike: dictation apps,
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meeting-notes tools, live captioning, voice-driven editors, or any pipeline
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that has to turn raw ASR output into text a person will read.
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It is a post-processing stage rather than a standalone system:
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```
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audio ──▶ ASR (Whisper, Parakeet, …) ──▶ S1-mini ──▶ clean text
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```
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The ASR's raw transcript becomes the transcript line, your app's settings
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[GGUF builds](https://huggingface.co/superwhisper/s1-mini-GGUF) exist for
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exactly that.
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+
Nothing about the model is Superwhisper-specific. The two things to get right
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in any integration are the input format documented above and the thinking
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flag; nearly every integration bug traces back to one of those.
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| 374 |
|
|
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> Read the [LICENSE](LICENSE) before you ship. Apache 2.0 is permissive but
|
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> not obligation-free: you must retain the license text and attribution
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> notices, and state significant changes if you redistribute a modified
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| 379 |
+
> version. It also carries one additional term: the model must keep its
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| 380 |
+
> name, "S1-mini" by "Superwhisper", with that exact capitalization,
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| 381 |
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> wherever it's used. If you are bundling S1-mini into a commercial
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> dictation app or redistributing the weights yourself, confirm the terms
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> cover your case rather than assuming they do.
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## License
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S1-mini is released under Apache 2.0, which it inherits from Qwen3-0.6B, plus
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+
one additional term: wherever it's used, it must keep its name, "S1-mini" by
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+
"Superwhisper", with that exact capitalization. See [LICENSE](LICENSE).
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## Citation
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```bibtex
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@misc{s1mini2026,
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title = {S1-mini: a small text normalizer for speech-to-text output},
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author = {Superwhisper},
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year = {2026},
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url = {https://huggingface.co/superwhisper/s1-mini}
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}
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