MLX
English
nima_joint_schema
tool-routing
decision-model
frozen-backbone
joint-schema
custom-code
research
Instructions to use neimand/nima with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use neimand/nima with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download neimand/nima --local-dir nima
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 391 Bytes
104376c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"protocol_id": "head-only-generalization-v2",
"seed": 42,
"train_views": 4,
"selection_views": 2,
"epochs": 80,
"batch_size": 8,
"learning_rate": 0.0003,
"weight_decay": 0.01,
"temperature": 1.0,
"selection": "minimum mean cross-entropy over the predeclared selection views",
"full_training_requires": "family-separated frozen dataset including confirmation split"
}
|