860eeab156bda8d3a05a696bb7ef6a8be13f9db34c23106a920f8dc36ba65ad9

README.md

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+---
+language:
+- en
+license: apache-2.0
+library_name: transformers
+tags:
+- mlx
+datasets:
+- HuggingFaceTB/smollm-corpus
+---
+
+# mlx-community/SmolLM-135M-4bit
+
+The Model [mlx-community/SmolLM-135M-4bit](https://huggingface.co/mlx-community/SmolLM-135M-4bit) was converted to MLX format from [HuggingFaceTB/SmolLM-135M](https://huggingface.co/HuggingFaceTB/SmolLM-135M) using mlx-lm version **0.16.0**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("mlx-community/SmolLM-135M-4bit")
+response = generate(model, tokenizer, prompt="hello", verbose=True)
+```

config.json

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+{
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 0,
+    "eos_token_id": 0,
+    "hidden_act": "silu",
+    "hidden_size": 576,
+    "initializer_range": 0.02,
+    "intermediate_size": 1536,
+    "max_position_embeddings": 2048,
+    "mlp_bias": false,
+    "model_type": "llama",
+    "num_attention_heads": 9,
+    "num_hidden_layers": 30,
+    "num_key_value_heads": 3,
+    "pretraining_tp": 1,
+    "quantization": {
+        "group_size": 64,
+        "bits": 4
+    },
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
+    "rope_theta": 10000.0,
+    "tie_word_embeddings": true,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.41.2",
+    "use_cache": true,
+    "vocab_size": 49152
+}

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