Text Generation
MLX
English
sol_milkshake
causal-lm
decoder-only
small-language-model
recurrent-depth
ngpt
research
Instructions to use solintellegence/Sol-Milkshake with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use solintellegence/Sol-Milkshake 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("solintellegence/Sol-Milkshake") 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 solintellegence/Sol-Milkshake with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "solintellegence/Sol-Milkshake" --prompt "Once upon a time"
- Atomic Chat
File size: 396 Bytes
7aa9bc4 cf5dd22 7aa9bc4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"architectures": ["SolMilkshake"],
"model_type": "sol_milkshake",
"model_name": "Sol Milkshake",
"parameter_count": 2990000,
"vocab_size": 2048,
"hidden_size": 192,
"max_position_embeddings": 2048,
"num_hidden_layers": 5,
"num_attention_heads": 6,
"num_key_value_heads": 2,
"head_dim": 32,
"intermediate_size": 512,
"tie_word_embeddings": true,
"framework": "mlx"
}
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