Text Generation
MLX
Safetensors
English
gpt_oss
apple-silicon
Mixture of Experts
mixture-of-experts
4-bit precision
quantized
gpt-oss
context-retrieval
Eval Results (legacy)
Instructions to use foadmk/context-1-MLX-MXFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use foadmk/context-1-MLX-MXFP4 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("foadmk/context-1-MLX-MXFP4") 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 foadmk/context-1-MLX-MXFP4 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "foadmk/context-1-MLX-MXFP4" --prompt "Once upon a time"
- Atomic Chat
Download tokenizer.json from foadmk/context-1-MLX-MXFP4: direct link, hf CLI and curl.
- Browser
- Download file 27.9 MB
-
https://huggingface.co/foadmk/context-1-MLX-MXFP4/resolve/main/tokenizer.json
- Command line
-
hf download hf://foadmk/context-1-MLX-MXFP4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/foadmk/context-1-MLX-MXFP4/resolve/main/tokenizer.json
27.9 MB
- Xet hash:
- 59f22360b51bf1a137fb80e14df310b4b249bed6cc64565aa0c401ca19ffcd04
- Size of remote file:
- 27.9 MB
- SHA256:
- 0614fe83cadab421296e664e1f48f4261fa8fef6e03e63bb75c20f38e37d07d3
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