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README.md

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+---
+language:
+- en
+tags:
+- mlx
+- apple-silicon
+- liquidai
+- lfm2
+- moe
+- transformer
+- long-context
+- instruct
+- quantized
+- 8bit
+- Mixture of Experts
+- coding
+- mlx
+- mlx-my-repo
+pipeline_tag: text-generation
+library_name: mlx
+license: other
+license_name: lfm1.0
+license_link: LICENSE
+base_model: mlx-community/LFM2-8B-A1B-8bit-MLX
+model-index:
+- name: LFM2-8B-A1B — MLX (Apple Silicon), **8-bit** (with guidance on MoE + RAM planning)
+  results: []
+---
+
+# introvoyz041/LFM2-8B-A1B-8bit-MLX-mlx-8Bit
+
+The Model [introvoyz041/LFM2-8B-A1B-8bit-MLX-mlx-8Bit](https://huggingface.co/introvoyz041/LFM2-8B-A1B-8bit-MLX-mlx-8Bit) was converted to MLX format from [mlx-community/LFM2-8B-A1B-8bit-MLX](https://huggingface.co/mlx-community/LFM2-8B-A1B-8bit-MLX) using mlx-lm version **0.28.3**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("introvoyz041/LFM2-8B-A1B-8bit-MLX-mlx-8Bit")
+
+prompt="hello"
+
+if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
+    messages = [{"role": "user", "content": prompt}]
+    prompt = tokenizer.apply_chat_template(
+        messages, tokenize=False, add_generation_prompt=True
+    )
+
+response = generate(model, tokenizer, prompt=prompt, verbose=True)
+```