Text Generation
MLX
Safetensors
Portuguese
mini-enedina
monotropic-model
small-language-model
structural-engineering
timoshenko-beam-theory
curriculum-learning
validated-synthetic-data
physics-informed-ai
apple-silicon
Instructions to use aiacontext/mini-enedina with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use aiacontext/mini-enedina 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("aiacontext/mini-enedina") 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 aiacontext/mini-enedina with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "aiacontext/mini-enedina" --prompt "Once upon a time"
- Atomic Chat
File size: 457 Bytes
bcd4a45 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"model_type": "mini-enedina",
"architectures": ["MiniEnedina"],
"dim": 512,
"n_layers": 7,
"n_heads": 8,
"head_dim": 64,
"intermediate_size": 2048,
"vocab_size": 8012,
"max_seq_len": 14336,
"norm_eps": 1e-5,
"rope_theta": 10000.0,
"normalization": "rmsnorm",
"activation": "silu_swiglu",
"positional_encoding": "rope",
"weight_tying": true,
"total_parameters": 37570000,
"framework": "mlx",
"torch_dtype": "bfloat16"
}
|