Instructions to use j0no12/nero-optimizer-work-simow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use j0no12/nero-optimizer-work-simow 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-simow") 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-simow 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-simow" --prompt "Once upon a time"
- Atomic Chat
Download state.json from j0no12/nero-optimizer-work-simow: direct link, hf CLI and curl.
- Browser
- Download file 61 Bytes
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https://huggingface.co/j0no12/nero-optimizer-work-simow/resolve/main/state.json
- Command line
-
hf download hf://j0no12/nero-optimizer-work-simow/state.json
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curl -L -o state.json https://huggingface.co/j0no12/nero-optimizer-work-simow/resolve/main/state.json
61 Bytes
| {"tokens_seen": 500000000, "step": 122071, "lr": 1.1025e-06} | |