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
- 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"
| { | |
| "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" | |
| } | |