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 inference_native/common.py from OpenSML/Solstice-1: direct link, hf CLI and curl.
- Browser
- Download file 250 Bytes
-
https://huggingface.co/OpenSML/Solstice-1/resolve/main/inference_native/common.py
- Command line
-
hf download hf://OpenSML/Solstice-1/inference_native/common.py
-
curl -L -o common.py https://huggingface.co/OpenSML/Solstice-1/resolve/main/inference_native/common.py
250 Bytes
| import hashlib | |
| import json | |
| from pathlib import Path | |
| def read_json(path): | |
| return json.loads(Path(path).read_text()) | |
| def file_sha256(path): | |
| with Path(path).open("rb") as stream: | |
| return hashlib.file_digest(stream,"sha256").hexdigest() | |