Text Generation
MLX
Safetensors
English
rodan-modern
rodan
tiny-language-model
reasoning
chain-of-thought
dpo
Instructions to use bfuzzy1/Rodan-Reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use bfuzzy1/Rodan-Reasoning with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("bfuzzy1/Rodan-Reasoning") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use bfuzzy1/Rodan-Reasoning with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "bfuzzy1/Rodan-Reasoning" --prompt "Once upon a time"
File size: 1,741 Bytes
b743d9d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | {
"model_type": "rodan-modern",
"architecture": "ModernLM",
"framework": "mlx",
"stage": "reasoning + DPO",
"base_model": "Rodan-10M-Chat (warm-start)",
"params": 10410000,
"vocab_size": 8194,
"dim": 320,
"n_layers": 8,
"n_heads": 8,
"n_kv_heads": 1,
"head_dim": 40,
"ffn_hidden": 768,
"max_len": 512,
"rope_base": 200000.0,
"norm": "rmsnorm",
"norm_eps": 1e-05,
"activation": "swiglu",
"qk_norm": true,
"tied_embeddings": true,
"value_residual": true,
"ple_rank": 0,
"lrm": true,
"recurse": 2,
"dtype": "bfloat16",
"attention": "mqa",
"chat_template": "chatml",
"chat_tokens": {
"im_start": 8192,
"im_end": 8193
},
"eot_id": 0,
"recommended_decode": "greedy, NO repetition penalty (it breaks the <think> format); stop on <|im_end|>",
"board_avg": 35.41,
"recipe": "v2 NL-balanced fold: 24% word-problems / 21% symbolic arith / 8% answer-only / 2% GSM8K / 45% replay",
"notes": "Warm-start from Rodan-10M-Chat, retrofitted recurrence (recurse=2 = 16 effective layers, 0 extra params). ChatML + <think> CoT. Load with ModernLM(ModernConfig(**fields, recurse=2)) + load_weights('model.safetensors'). Prompt: <|im_start|>user\\n{q}<|im_end|>\\n<|im_start|>assistant\\n ; emits <think>steps</think> then answer for math, often direct for simple facts. Board 35.41 (level w/ base v6 35.80) \u2014 value is reasoning BEHAVIOUR (accurate arith, word-problem translation, answers facts directly after DPO), not board rank. Final stage = DPO (see dpo field).",
"dpo": "verifiable preference pairs (mode: direct\u227bneedless-think ; process: correct\u227bwrong-chain), KL-leashed beta=0.1 lr=5e-7 1ep \u2014 fixed restraint (math-on-non-math ~4/8\u2192~1/8), board held"
} |