Instructions to use whisperstream/stream-1-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use whisperstream/stream-1-mini with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf whisperstream/stream-1-mini:F16
# Run inference directly in the terminal:
llama cli -hf whisperstream/stream-1-mini:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf whisperstream/stream-1-mini:F16
# Run inference directly in the terminal:
llama cli -hf whisperstream/stream-1-mini:F16

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf whisperstream/stream-1-mini:F16
# Run inference directly in the terminal:
./llama-cli -hf whisperstream/stream-1-mini:F16

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf whisperstream/stream-1-mini:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf whisperstream/stream-1-mini:F16

Use Docker

docker model run hf.co/whisperstream/stream-1-mini:F16

Llama new
LM Studio
Jan

vLLM

How to use whisperstream/stream-1-mini with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "whisperstream/stream-1-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": "whisperstream/stream-1-mini",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/whisperstream/stream-1-mini:F16

Ollama
How to use whisperstream/stream-1-mini with Ollama:
```
ollama run hf.co/whisperstream/stream-1-mini:F16
```
Unsloth Desktop
Docker Model Runner
How to use whisperstream/stream-1-mini with Docker Model Runner:
```
docker model run hf.co/whisperstream/stream-1-mini:F16
```

Lemonade

How to use whisperstream/stream-1-mini with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull whisperstream/stream-1-mini:F16

Run and chat with the model

lemonade run user.stream-1-mini-F16

List all available models

lemonade list

Atomic Chat

stream-1-mini

File size: 998 Bytes

{
  "candidate": "balanced-seed23-terminal648",
  "previous_hub_revision": "7a7b7101f8fe056fb7db978dca58eff839d6f58e",
  "q4_sha256": "32bef61bdbc98787ac278d96a2aad120a9fc61f588f1f0a4746441e9d6d89ae7",
  "f16_sha256": "79ec0a69386ef593bdea5f120fdd4201298d09efaac7a6aafffdb4ee615a2cdf",
  "prompt_sha256": {
    "chat": "3555c01ea0594a448603b61d6b08c5bb425e99fb0b5ac43f2a13a2c08bdd1f90",
    "email": "4d89ee2930d7c2e2479b9b7ae472fc65919fde500ea915206b87f802f2fe2bad"
  },
  "decoder": {
    "temperature": 0,
    "top_k": 1,
    "top_p": 1,
    "repeat_penalty": 1,
    "max_tokens": 512,
    "cache_prompt": true,
    "chat_template_kwargs": {
      "enable_thinking": false
    }
  },
  "vocabulary_helper_sha256": "bd8c22d94aee081406847ee84ece27578cc7a3e57a7c0d8387600149b90a589d",
  "full_observed_regression_requests": 3409,
  "fresh_confirmation_performed": false,
  "fresh_confirmation_waived": true,
  "known_regressions_and_unresolved_judgments_retained": true
}