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/manifest.json from OpenSML/Solstice-1: direct link, hf CLI and curl.
- Browser
- Download file 988 Bytes
-
https://huggingface.co/OpenSML/Solstice-1/resolve/main/tokenizer/manifest.json
- Command line
-
hf download hf://OpenSML/Solstice-1/tokenizer/manifest.json
-
curl -L -o manifest.json https://huggingface.co/OpenSML/Solstice-1/resolve/main/tokenizer/manifest.json
988 Bytes
| { | |
| "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": [ | |
| "<|pad|>", | |
| "<|doc_end|>", | |
| "<|turn_start|>", | |
| "<|turn_end|>" | |
| ], | |
| "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 | |
| } | |