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 # tiny
 
-A four-bit quantised conversion of [`mlx-community/SmolLM-135M-Instruct-4bit`](https://huggingface.co/mlx-community/SmolLM-135M-Instruct-4bit), produced with `mlx-lm` 0.30.4 and intended for Apple Silicon. The architecture is a Llama variant — thirty layers, 576 hidden dimensions, nine attention heads, three key-value heads, 49152-token vocabulary — with group-size 64 four-bit weights, occupying about 76 MB.
+A four-bit quantised conversion of [`mlx-community/SmolLM-135M-Instruct-4bit`](https://huggingface.co/mlx-community/SmolLM-135M-Instruct-4bit), produced with `mlx-lm` 0.30.4 and intended for Apple Silicon. The architecture is a Llama variant (thirty layers, 576 hidden dimensions, nine attention heads, three key-value heads, 49152-token vocabulary) with group-size 64 four-bit weights, occupying about 76 MB.
 
 The `model.safetensors.index.json` alongside the weights is not a sharded checkpoint here; it maps all 694 tensors onto the single `model.safetensors` file that sits beside it.
 
-Because the weights are quantised, `transformers` cannot load this checkpoint — it needs `mlx-lm`, which applies the group quantisation at load time. The instruction tuning lives upstream in SmolLM; this repository adds a format, nothing else. Given the size, expect it to be fast and largely incoherent on factual questions.
+Because the weights are quantised, `transformers` cannot load this checkpoint; it needs `mlx-lm`, which applies the group quantisation at load time. The instruction tuning lives upstream in SmolLM; this repository adds a format, nothing else. Given the size, expect it to be fast and largely incoherent on factual questions.
 
 ## Usage