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- d08d7d656c9582522d1aff8b8336aa796b0225d706cc62e1ea5ddc7f8d894d6e (c1974ca923f1e432254477b5d6b7c7cd9a24e360)

README.md

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+---
+base_model: amd/AMD-Llama-135m-code
+datasets:
+- cerebras/SlimPajama-627B
+- manu/project_gutenberg
+license: apache-2.0
+tags:
+- mlx
+---
+
+# mlx-community/AMD-Llama-135m-code-float32
+
+The Model [mlx-community/AMD-Llama-135m-code-float32](https://huggingface.co/mlx-community/AMD-Llama-135m-code-float32) was converted to MLX format from [amd/AMD-Llama-135m-code](https://huggingface.co/amd/AMD-Llama-135m-code) using mlx-lm version **0.18.2**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("mlx-community/AMD-Llama-135m-code-float32")
+
+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)
+```

config.json

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+    "intermediate_size": 2048,
+    "max_position_embeddings": 2048,
+    "model_type": "llama",
+    "num_attention_heads": 12,
+    "num_hidden_layers": 12,
+    "num_key_value_heads": 12,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
+    "rope_theta": 10000.0,
+    "tie_word_embeddings": false,
+    "torch_dtype": "float32",
+    "transformers_version": "4.36.2",
+    "use_cache": true,
+    "vocab_size": 32000
+}

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