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- d4bf42ed9d2b35f291bb3a386555ccd777e860fc28098238e99f5d31774a699e (ae6ae6bb88f04bffa2fdd42f4f55164c6fe688fb)

README.md

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+---
+license: apache-2.0
+base_model: unsloth/SmolLM-360M
+tags:
+- alignment-handbook
+- trl
+- unsloth
+- mlx
+datasets:
+- Magpie-Align/Magpie-Pro-300K-Filtered
+- bigcode/self-oss-instruct-sc2-exec-filter-50k
+- teknium/OpenHermes-2.5
+- HuggingFaceTB/everyday-conversations-llama3.1-2k
+library_name: transformers
+language:
+- en
+---
+
+# shashikanth-a/SmolLM-360M-4bit
+
+The Model [shashikanth-a/SmolLM-360M-4bit](https://huggingface.co/shashikanth-a/SmolLM-360M-4bit) was converted to MLX format from [unsloth/SmolLM-360M](https://huggingface.co/unsloth/SmolLM-360M) using mlx-lm version **0.19.3**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("shashikanth-a/SmolLM-360M-4bit")
+
+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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+{
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 0,
+    "eos_token_id": 0,
+    "hidden_act": "silu",
+    "hidden_size": 960,
+    "initializer_range": 0.02,
+    "intermediate_size": 2560,
+    "max_position_embeddings": 2048,
+    "mlp_bias": false,
+    "model_type": "llama",
+    "num_attention_heads": 15,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 5,
+    "pretraining_tp": 1,
+    "quantization": {
+        "group_size": 64,
+        "bits": 4
+    },
+    "quantization_config": {
+        "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": "4.44.2",
+    "use_cache": true,
+    "vocab_size": 49152
+}

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