Instructions to use j0no12/nero-optimizer-work-simo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use j0no12/nero-optimizer-work-simo 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("j0no12/nero-optimizer-work-simo") 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 j0no12/nero-optimizer-work-simo with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "j0no12/nero-optimizer-work-simo" --prompt "Once upon a time"
- Atomic Chat
Download config.json from j0no12/nero-optimizer-work-simo: direct link, hf CLI and curl.
- Browser
- Download file 914 Bytes
-
https://huggingface.co/j0no12/nero-optimizer-work-simo/resolve/main/config.json
- Command line
-
hf download hf://j0no12/nero-optimizer-work-simo/config.json
-
curl -L -o config.json https://huggingface.co/j0no12/nero-optimizer-work-simo/resolve/main/config.json
914 Bytes
| { | |
| "model_type": "nero_dense_control_mlx", | |
| "architectures": [ | |
| "DenseControlLM" | |
| ], | |
| "framework": "mlx", | |
| "optimizer": "simo", | |
| "vocab_size": 2048, | |
| "context_length": 128, | |
| "width": 128, | |
| "blocks": 6, | |
| "head_dim": 32, | |
| "mlp_width": 148, | |
| "stored_parameters": 999680, | |
| "training_tokens": 500000000, | |
| "batch_size": 32, | |
| "requested_learning_rate": null, | |
| "momentum_beta": null, | |
| "source_run": "mlx_simo_500m_ctx128", | |
| "checkpoint": "checkpoint_000500000000", | |
| "metrics": { | |
| "final_train_loss": 4.8593268394470215, | |
| "final_tokens_seen": 500000000, | |
| "final_step": 122071, | |
| "final_tokens_per_second": 420823.9883475866, | |
| "tail_median_tokens_per_second": 420811.12713801593, | |
| "logged_metric_rows": 1221 | |
| }, | |
| "final_log_row": { | |
| "step": 122071, | |
| "tokens_seen": 500000000, | |
| "loss": 4.8593268394470215, | |
| "lr": 1.05e-06, | |
| "tokens_per_second": 420823.9883475866 | |
| } | |
| } | |