Text Generation
MLX
English
German
next-concept-modeling
apple-silicon
diffusion-lm
research-code
negative-results
Instructions to use Red-fuchs/ncm-modular with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Red-fuchs/ncm-modular 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("Red-fuchs/ncm-modular") 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 Red-fuchs/ncm-modular with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "Red-fuchs/ncm-modular" --prompt "Once upon a time"
- Atomic Chat
Download src/ncm_modular/__pycache__/masking.cpython-312.pyc from Red-fuchs/ncm-modular: direct link, hf CLI and curl.
- Browser
- Download file 4.85 kB
-
https://huggingface.co/Red-fuchs/ncm-modular/resolve/main/src/ncm_modular/__pycache__/masking.cpython-312.pyc
- Command line
-
hf download hf://Red-fuchs/ncm-modular/src/ncm_modular/__pycache__/masking.cpython-312.pyc
-
curl -L -o masking.cpython-312.pyc https://huggingface.co/Red-fuchs/ncm-modular/resolve/main/src/ncm_modular/__pycache__/masking.cpython-312.pyc
4.85 kB
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