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README.md

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+---
+library_name: transformers
+tags:
+- mlx
+base_model: state-spaces/mamba-130m-hf
+---
+
+# mlx-community/mamba-130m-hf-4-bit
+
+The Model [mlx-community/mamba-130m-hf-4-bit](https://huggingface.co/mlx-community/mamba-130m-hf-4-bit) was converted to MLX format from [state-spaces/mamba-130m-hf](https://huggingface.co/state-spaces/mamba-130m-hf) using mlx-lm version **0.18.1**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("mlx-community/mamba-130m-hf-4-bit")
+response = generate(model, tokenizer, prompt="hello", verbose=True)
+```

config.json

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+{
+    "architectures": [
+        "MambaForCausalLM"
+    ],
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+    "conv_kernel": 4,
+    "d_inner": 1536,
+    "d_model": 768,
+    "eos_token_id": 0,
+    "expand": 2,
+    "fused_add_norm": true,
+    "hidden_act": "silu",
+    "hidden_size": 768,
+    "initializer_range": 0.1,
+    "intermediate_size": 1536,
+    "layer_norm_epsilon": 1e-05,
+    "model_type": "mamba",
+    "n_layer": 24,
+    "num_hidden_layers": 24,
+    "pad_token_id": 0,
+    "pad_vocab_size_multiple": 8,
+    "rescale_prenorm_residual": false,
+    "residual_in_fp32": true,
+    "rms_norm": true,
+    "ssm_cfg": {},
+    "state_size": 16,
+    "time_step_floor": 0.0001,
+    "time_step_init_scheme": "random",
+    "time_step_max": 0.1,
+    "time_step_min": 0.001,
+    "time_step_rank": 48,
+    "time_step_scale": 1.0,
+    "torch_dtype": "float32",
+    "transformers_version": "4.39.0.dev0",
+    "use_bias": false,
+    "use_cache": true,
+    "use_conv_bias": true,
+    "vocab_size": 50280
+}

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