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
Download tokenizer/report.json from OpenSML/Solstice-1: direct link, hf CLI and curl.
- Browser
- Download file 889 Bytes
-
https://huggingface.co/OpenSML/Solstice-1/resolve/main/tokenizer/report.json
- Command line
-
hf download hf://OpenSML/Solstice-1/tokenizer/report.json
-
curl -L -o report.json https://huggingface.co/OpenSML/Solstice-1/resolve/main/tokenizer/report.json
889 Bytes
| { | |
| "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 | |
| } | |