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/FINAL_COMPARISON.json from OpenSML/Solstice-1: direct link, hf CLI and curl.
- Browser
- Download file 9.42 kB
-
https://huggingface.co/OpenSML/Solstice-1/resolve/main/results/FINAL_COMPARISON.json
- Command line
-
hf download hf://OpenSML/Solstice-1/results/FINAL_COMPARISON.json
-
curl -L -o FINAL_COMPARISON.json https://huggingface.co/OpenSML/Solstice-1/resolve/main/results/FINAL_COMPARISON.json
9.42 kB
| { | |
| "attempt": 4, | |
| "checkpoint": "${WORKSPACE}/pretraining/runs/deep44_chat_repair_04_20261109/step_0000128_5937a6def881", | |
| "comparisons": [ | |
| { | |
| "baseline": "parent2000", | |
| "confidence_interval_97_5": [ | |
| 0.2868590999102137, | |
| 0.3503937996078803 | |
| ], | |
| "gain": 0.319, | |
| "gained": 331, | |
| "lost": 12, | |
| "method": "Scenario-cluster paired percentile bootstrap, 10000 draws; 97.5% interval for each of two baseline comparisons. Covers sampling uncertainty within this authored panel, not all chat tasks." | |
| }, | |
| { | |
| "baseline": "attempt5", | |
| "confidence_interval_97_5": [ | |
| 0.22927273486383004, | |
| 0.2900111982191158 | |
| ], | |
| "gain": 0.26, | |
| "gained": 266, | |
| "lost": 6, | |
| "method": "Scenario-cluster paired percentile bootstrap, 10000 draws; 97.5% interval for each of two baseline comparisons. Covers sampling uncertainty within this authored panel, not all chat tasks." | |
| } | |
| ], | |
| "legacy_test": { | |
| "assistant_nll": 1.0202431740774651, | |
| "components": { | |
| "constraints": 0.37785995097947306, | |
| "dialogue": 0.6084018315086723, | |
| "general": 1.7695224359631538, | |
| "grounded": 0.44701617732062005, | |
| "knowledge": 1.3031791490502656, | |
| "rewrite": 1.2700324356555939, | |
| "skills": 0.9353672320915697, | |
| "social": 1.450566180050373 | |
| }, | |
| "empty_rate": 0.0, | |
| "generated_counts": { | |
| "constraints": 128, | |
| "dialogue": 128, | |
| "grounded": 128, | |
| "knowledge": 128, | |
| "skills": 192 | |
| }, | |
| "generated_macro_pass": 0.5598958333333334, | |
| "generated_pass_counts": { | |
| "constraints": 109, | |
| "dialogue": 114, | |
| "grounded": 68, | |
| "knowledge": 26, | |
| "skills": 62 | |
| }, | |
| "generated_rates": { | |
| "constraints": 0.8515625, | |
| "dialogue": 0.890625, | |
| "grounded": 0.53125, | |
| "knowledge": 0.203125, | |
| "skills": 0.3229166666666667 | |
| }, | |
| "natural_stop": 0.9865591397849462, | |
| "precision": "exact-fp32-masters", | |
| "qualitative_count": 40, | |
| "repetition_rate": 0.020161290322580645, | |
| "replacement_character_rate": 0.0, | |
| "retention": { | |
| "sources": { | |
| "dclm": 2.9645858108997345, | |
| "web": 2.8973595052957535, | |
| "wiki": 2.422679301351309 | |
| }, | |
| "val_loss": 2.8633367460221053, | |
| "validation_fingerprint": "2e9444ddc7de3cf4685911d967c1ad605d9b8cfd9244f7039621e828bf088ffa" | |
| }, | |
| "scope": "Checked grounded answers, deterministic tasks and authored conversation context. Public general/dialogue/social outputs require semantic review. No code, SQL, JSON, or public benchmark scores select checkpoints.", | |
| "split": "test", | |
| "step": 128, | |
| "stop_reason_counts": { | |
| "token_limit": 10, | |
| "turn_end": 734 | |
| }, | |
| "turn_end_rate": 0.9865591397849462 | |
| }, | |
| "new_test": { | |
| "correct": 519, | |
| "counts": { | |
| "abstention": 172, | |
| "constraints": 25, | |
| "dialogue": 194, | |
| "grounded": 81, | |
| "reasoning": 47 | |
| }, | |
| "empty": 0, | |
| "false_abstention_signals": 111, | |
| "identity": { | |
| "data": "abcdf03853c4f00fff1e92cdf5f98d8ee3bea42526c18f15585650b368ddd2f3", | |
| "evaluator": "40dbfada2856c91b0a7ffe5df7b9584175dbd479a1c6b581d1935d38dd6228aa", | |
| "parent": "2118c7446c412a4ee7a4b7a356a211ad91574983e213da45980707b5fa1ca124" | |
| }, | |
| "missing_fact_abstention_signals": 183, | |
| "natural_stop": 1.0, | |
| "repetition_rate": 0.0, | |
| "scoring": "Conservative whole-answer equivalence for factual tasks; exact format for transformation tasks. Strict format compliance is reported separately. Whole-passage copying and contradictory extra claims are not accepted.", | |
| "strict_correct": 518, | |
| "strict_counts": { | |
| "abstention": 172, | |
| "constraints": 25, | |
| "dialogue": 194, | |
| "grounded": 80, | |
| "reasoning": 47 | |
| }, | |
| "total": 1000, | |
| "totals": { | |
| "abstention": 200, | |
| "constraints": 200, | |
| "dialogue": 200, | |
| "grounded": 200, | |
| "reasoning": 200 | |
| } | |
| }, | |
| "preserved": true, | |
| "public": { | |
| "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": 26, | |
| "answer_match_with_neutral_wrapper": 26, | |
| "clean_response": 30, | |
| "count": 30, | |
| "empty": 0, | |
| "natural_stop": 30, | |
| "repeated": 0, | |
| "strict_task_success": 26, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| }, | |
| "instructions": { | |
| "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 | |
| }, | |
| "knowledge": { | |
| "answer_match": 16, | |
| "answer_match_with_neutral_wrapper": 16, | |
| "clean_response": 30, | |
| "count": 30, | |
| "empty": 0, | |
| "natural_stop": 30, | |
| "repeated": 0, | |
| "strict_task_success": 16, | |
| "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": 107, | |
| "answer_match_with_neutral_wrapper": 107, | |
| "clean_response": 180, | |
| "count": 180, | |
| "empty": 0, | |
| "natural_stop": 180, | |
| "repeated": 0, | |
| "strict_task_success": 107, | |
| "token_limit": 0, | |
| "unexpected_structure": 0 | |
| }, | |
| "response_control_all": { | |
| "answer_match": 107, | |
| "answer_match_with_neutral_wrapper": 107, | |
| "clean_response": 189, | |
| "count": 192, | |
| "empty": 0, | |
| "natural_stop": 191, | |
| "repeated": 3, | |
| "strict_task_success": 107, | |
| "token_limit": 1, | |
| "unexpected_structure": 0 | |
| } | |
| }, | |
| "choices": { | |
| "arc_challenge": { | |
| "acc": 0.2935153583617747, | |
| "acc_norm": 0.30887372013651876, | |
| "complete": true, | |
| "context_truncated_choices": 0, | |
| "evaluated": 1172, | |
| "expected": 1172 | |
| }, | |
| "arc_easy": { | |
| "acc": 0.6258417508417509, | |
| "acc_norm": 0.6233164983164983, | |
| "complete": true, | |
| "context_truncated_choices": 0, | |
| "evaluated": 2376, | |
| "expected": 2376 | |
| }, | |
| "hellaswag": { | |
| "acc": 0.3285202150965943, | |
| "acc_norm": 0.39404501095399325, | |
| "complete": true, | |
| "context_truncated_choices": 0, | |
| "evaluated": 10042, | |
| "expected": 10042 | |
| }, | |
| "piqa": { | |
| "acc": 0.6648531011969532, | |
| "acc_norm": 0.6621327529923831, | |
| "complete": true, | |
| "context_truncated_choices": 0, | |
| "evaluated": 1838, | |
| "expected": 1838 | |
| } | |
| }, | |
| "complete": true, | |
| "ifeval": { | |
| "loose": { | |
| "instruction_accuracy": 0.3249400479616307, | |
| "instructions": 834, | |
| "prompt_accuracy": 0.1922365988909427, | |
| "prompts": 541 | |
| }, | |
| "strict": { | |
| "instruction_accuracy": 0.3009592326139089, | |
| "instructions": 834, | |
| "prompt_accuracy": 0.17929759704251386, | |
| "prompts": 541 | |
| } | |
| }, | |
| "model_sha256": "7b2d8777040f05d8e0849acac4e45013b2de3d72145c363cd22825e80115c515" | |
| }, | |
| "reasons": [], | |
| "scope": "One dev-selected finalist; reserved authored task panel is not a complete measure of conversational quality. Public and historical suites were already used in earlier experiments.", | |
| "significant_on_reserved_panel_and_passed_guards": true | |
| } | |