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: 670 Bytes
7aa9bc4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"release_checkpoint": "checkpoint_000900005888",
"base_pretraining_tokens": 1626560000,
"recovery_tokens": 900005888,
"total_token_exposures": 2526565888,
"recovery_peak_learning_rate": 0.000005,
"recovery_terminal_learning_rate": 0.0000005,
"recovery_mixture": {
"original_curriculum": 0.70,
"cosmopedia_v2_english": 0.15,
"finephrase": 0.15
},
"recovery_context": {
"initial_phase": "75% 512 / 25% 1024",
"final_400982016_tokens": "512 only"
},
"optimizer": "nGPT-aware AdamW",
"seed": 20260920,
"weight_format": "MLX NPZ",
"selection_note": "Selected from recovery checkpoints using the reported evaluation suite."
}
|