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 results/baselines/attempt5.json from OpenSML/Solstice-1: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/OpenSML/Solstice-1/resolve/main/results/baselines/attempt5.json
- Command line
-
hf download hf://OpenSML/Solstice-1/results/baselines/attempt5.json
-
curl -L -o attempt5.json https://huggingface.co/OpenSML/Solstice-1/resolve/main/results/baselines/attempt5.json
4.79 kB
| { | |
| "chat": { | |
| "answerability": { | |
| "False": { | |
| "answer_match": 0, | |
| "answer_match_with_neutral_wrapper": 0, | |
| "clean_response": 15, | |
| "count": 15, | |
| "empty": 0, | |
| "natural_stop": 15, | |
| "repeated": 0, | |
| "strict_task_success": 0, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| }, | |
| "True": { | |
| "answer_match": 12, | |
| "answer_match_with_neutral_wrapper": 12, | |
| "clean_response": 15, | |
| "count": 15, | |
| "empty": 0, | |
| "natural_stop": 15, | |
| "repeated": 0, | |
| "strict_task_success": 12, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| } | |
| }, | |
| "categories": { | |
| "answerability": { | |
| "answer_match": 12, | |
| "answer_match_with_neutral_wrapper": 12, | |
| "clean_response": 30, | |
| "count": 30, | |
| "empty": 0, | |
| "natural_stop": 30, | |
| "repeated": 0, | |
| "strict_task_success": 12, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| }, | |
| "conversation": { | |
| "answer_match": 25, | |
| "answer_match_with_neutral_wrapper": 25, | |
| "clean_response": 30, | |
| "count": 30, | |
| "empty": 0, | |
| "natural_stop": 30, | |
| "repeated": 0, | |
| "strict_task_success": 25, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| }, | |
| "instructions": { | |
| "answer_match": 11, | |
| "answer_match_with_neutral_wrapper": 11, | |
| "clean_response": 30, | |
| "count": 30, | |
| "empty": 0, | |
| "natural_stop": 30, | |
| "repeated": 0, | |
| "strict_task_success": 11, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| }, | |
| "knowledge": { | |
| "answer_match": 15, | |
| "answer_match_with_neutral_wrapper": 15, | |
| "clean_response": 30, | |
| "count": 30, | |
| "empty": 0, | |
| "natural_stop": 30, | |
| "repeated": 0, | |
| "strict_task_success": 15, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| }, | |
| "reading": { | |
| "answer_match": 27, | |
| "answer_match_with_neutral_wrapper": 27, | |
| "clean_response": 30, | |
| "count": 30, | |
| "empty": 0, | |
| "natural_stop": 30, | |
| "repeated": 0, | |
| "strict_task_success": 27, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| }, | |
| "reasoning": { | |
| "answer_match": 11, | |
| "answer_match_with_neutral_wrapper": 11, | |
| "clean_response": 30, | |
| "count": 30, | |
| "empty": 0, | |
| "natural_stop": 30, | |
| "repeated": 0, | |
| "strict_task_success": 11, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| } | |
| }, | |
| "caveat": "Answer match is conservative automatic scoring, not a complete semantic correctness judgment. Non-matching answers and open chat require review. Repetition detection is heuristic.", | |
| "objective": { | |
| "answer_match": 101, | |
| "answer_match_with_neutral_wrapper": 101, | |
| "clean_response": 180, | |
| "count": 180, | |
| "empty": 0, | |
| "natural_stop": 180, | |
| "repeated": 0, | |
| "strict_task_success": 101, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| }, | |
| "response_control_all": { | |
| "answer_match": 101, | |
| "answer_match_with_neutral_wrapper": 101, | |
| "clean_response": 190, | |
| "count": 192, | |
| "empty": 0, | |
| "natural_stop": 191, | |
| "repeated": 2, | |
| "strict_task_success": 101, | |
| "token_limit": 1, | |
| "unexpected_structure": 0 | |
| } | |
| }, | |
| "choices": { | |
| "arc_challenge": { | |
| "acc": 0.2901023890784983, | |
| "acc_norm": 0.3122866894197952, | |
| "complete": true, | |
| "context_truncated_choices": 0, | |
| "evaluated": 1172, | |
| "expected": 1172 | |
| }, | |
| "arc_easy": { | |
| "acc": 0.6300505050505051, | |
| "acc_norm": 0.6233164983164983, | |
| "complete": true, | |
| "context_truncated_choices": 0, | |
| "evaluated": 2376, | |
| "expected": 2376 | |
| }, | |
| "hellaswag": { | |
| "acc": 0.329416450906194, | |
| "acc_norm": 0.394443337980482, | |
| "complete": true, | |
| "context_truncated_choices": 0, | |
| "evaluated": 10042, | |
| "expected": 10042 | |
| }, | |
| "piqa": { | |
| "acc": 0.6632208922742111, | |
| "acc_norm": 0.6643090315560392, | |
| "complete": true, | |
| "context_truncated_choices": 0, | |
| "evaluated": 1838, | |
| "expected": 1838 | |
| } | |
| }, | |
| "complete": true, | |
| "ifeval": { | |
| "loose": { | |
| "instruction_accuracy": 0.30335731414868106, | |
| "instructions": 834, | |
| "prompt_accuracy": 0.1645101663585952, | |
| "prompts": 541 | |
| }, | |
| "strict": { | |
| "instruction_accuracy": 0.28177458033573144, | |
| "instructions": 834, | |
| "prompt_accuracy": 0.15526802218114602, | |
| "prompts": 541 | |
| } | |
| }, | |
| "model_sha256": "2cba542e887527a294bf8435d59015318dbeb3f58503d075abe14c90775b5ab0" | |
| } | |