Text Generation
MLX
Safetensors
English
rodan-modern
rodan
tiny-language-model
apple-silicon
byte-bpe
Instructions to use bfuzzy1/Rodan-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use bfuzzy1/Rodan-Base 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-Base") 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-Base 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-Base" --prompt "Once upon a time"
File size: 674 Bytes
d62ba2f | 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 | {
"model_type": "rodan-modern",
"architecture": "ModernLM",
"framework": "mlx",
"params": 11460000,
"vocab_size": 8192,
"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-5,
"activation": "swiglu",
"qk_norm": true,
"tied_embeddings": true,
"value_residual": true,
"ple_rank": 16,
"lrm": true,
"attention": "mqa",
"tokenizer": "byte-level BPE (8k), eot id 0",
"notes": "Custom MLX decoder-only transformer. Load with model_opt.ModernLM(ModernConfig(**fields)) + load_weights('model.safetensors'). See README."
}
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