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"
| { | |
| "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." | |
| } | |