Text Generation
MLX
Safetensors
English
small-language-model
from-scratch
conversational
apple-silicon
research
Instructions to use OpenSML/Solstice-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use OpenSML/Solstice-1 with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("OpenSML/Solstice-1") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use OpenSML/Solstice-1 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "OpenSML/Solstice-1"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "OpenSML/Solstice-1" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenSML/Solstice-1", "messages": [ {"role": "user", "content": "Hello"} ] }' - Atomic Chat
File size: 1,269 Bytes
7bcd331 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
"date": "2026-11-09",
"model": "OpenSML/Solstice-1",
"parameter_label": "175M",
"parameters": 174202432,
"status": "passed",
"weight_sha256": "7b2d8777040f05d8e0849acac4e45013b2de3d72145c363cd22825e80115c515",
"environment": {
"python": "3.11.13",
"macos": "27.0.1",
"machine": "arm64",
"mlx": "0.32.3",
"numpy": "2.4.2",
"tokenizers": "0.22.2"
},
"clean_environment": true,
"external_working_directory": true,
"inference_dependencies_from_training_checkout": false,
"saved_responses_matched": 27,
"saved_responses_checked": 27,
"checks": [
"Tokenizer round trips and literal structural-token isolation",
"Explicit chat token boundaries",
"Invalid roles, empty messages and turn orders rejected",
"Output budget bounds and context overflow rejected",
"Non-finite and out-of-range temperatures rejected",
"Fixed-seed sampling is repeatable in this runtime"
],
"full_public_suite_rerun": false,
"public_suite_evidence": "Previously completed full public suite on the identical FP32 tensor file.",
"details": "results/package_inference_verification.json",
"training_reproduction": "Not rerun. Historical sources/configs are an audit archive with documented external prerequisites."
}
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