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: 889 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 35 36 37 38 39 | {
"fixtures_passed": 9,
"sources": {
"cosmopedia": {
"bytes": 402259,
"bytes_per_token": 5.061007523716062,
"documents": 103,
"roundtrip_failures": 0,
"seconds": 0.09366637503262609,
"tokens": 79482
},
"dclm": {
"bytes": 1001509,
"bytes_per_token": 4.453209483494593,
"documents": 165,
"roundtrip_failures": 0,
"seconds": 0.26016941701527685,
"tokens": 224896
},
"web": {
"bytes": 2205062,
"bytes_per_token": 4.625467253451697,
"documents": 559,
"roundtrip_failures": 0,
"seconds": 0.5487007499905303,
"tokens": 476722
},
"wiki": {
"bytes": 401775,
"bytes_per_token": 4.059276397546905,
"documents": 143,
"roundtrip_failures": 0,
"seconds": 0.10723229206632823,
"tokens": 98977
}
},
"vocab_size": 32000
}
|