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: 988 Bytes
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"boundary_policy": "raw-text-then-one-document-EOS-v1",
"corpus_fingerprint": "a89f69d6f63cfa4385da233693a445404234a18194170fe1d2b4a74bf501f5d6",
"format": "sml-v2-tokenizer-v1",
"recipe": {
"corpus": "a89f69d6f63cfa4385da233693a445404234a18194170fe1d2b4a74bf501f5d6",
"min_frequency": 2,
"sample_manifest": "30ead6f502f11e99b479e3711a81ce7198787408d0700153615fc3255b244f46",
"specials": [
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"<|turn_start|>",
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],
"tokenizers": "0.22.2",
"version": 1,
"vocab_size": 32000
},
"sha256": {
"corpus.json": "e4c47b7b6aba08f948de7c2c7cb94c58dbd09dde2ded6ac185c60856ee686d27",
"tokenizer.json": "e095f0413a11fa91fbb58f37d00e4c6bcda59beb89b28f6f680db1436a7e8891",
"tokenizer_config.json": "619f500553367eb76f5be00a98625130ec857b9c367561334984096c029ba2a9"
},
"special_ids": {
"eos": 1,
"pad": 0,
"turn_end": 3,
"turn_start": 2
},
"vocab_size": 32000
}
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