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
Download release_checks.json from neimand/nima: direct link, hf CLI and curl.
- Browser
- Download file 357 Bytes
-
https://huggingface.co/neimand/nima/resolve/main/release_checks.json
- Command line
-
hf download hf://neimand/nima/release_checks.json
-
curl -L -o release_checks.json https://huggingface.co/neimand/nima/resolve/main/release_checks.json
357 Bytes
| { | |
| "head_parameter_count_from_safetensors_header": 1318657, | |
| "original_head_sha256_verified": true, | |
| "encoding_functions_copied_verbatim": [ | |
| "choices", | |
| "encode" | |
| ], | |
| "no_training_or_inference_performed_for_release": true, | |
| "encoding_parity_cases": 2048, | |
| "python_syntax": true, | |
| "import_without_mlx": true, | |
| "length_limit_verified": true | |
| } | |