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Model: moutons/Llama-3.1-Swallow-JP-EN-Translator-v1-8B-mlx-fp16
Source: Original Platform

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README.md

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+---
+base_model: mpasila/Llama-3.1-Swallow-JP-EN-Translator-v1-8B
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- llama
+- mlx
+- mlx-my-repo
+license:
+- llama3.3
+- gemma
+language:
+- en
+- ja
+datasets:
+- mpasila/ParallelFiction-Ja_En-1k-16k-Gemma-3-ShareGPT-Filtered
+- NilanE/ParallelFiction-Ja_En-100k
+---
+
+# moutons/Llama-3.1-Swallow-JP-EN-Translator-v1-8B-mlx-fp16
+
+The Model [moutons/Llama-3.1-Swallow-JP-EN-Translator-v1-8B-mlx-fp16](https://huggingface.co/moutons/Llama-3.1-Swallow-JP-EN-Translator-v1-8B-mlx-fp16) was converted to MLX format from [mpasila/Llama-3.1-Swallow-JP-EN-Translator-v1-8B](https://huggingface.co/mpasila/Llama-3.1-Swallow-JP-EN-Translator-v1-8B) using mlx-lm version **0.31.2**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("moutons/Llama-3.1-Swallow-JP-EN-Translator-v1-8B-mlx-fp16")
+
+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)
+```

chat_template.jinja

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+{% for message in messages %}{% if message['role'] == 'user' %}{{'<|im_start|>user
+' + message['content'] + '<|im_end|>
+'}}{% elif message['role'] == 'assistant' %}{{'<|im_start|>assistant
+' + message['content'] + '<|im_end|>
+' }}{% else %}{{ '<|im_start|>system
+' + message['content'] + '<|im_end|>
+' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
+' }}{% endif %}

config.json

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+{
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 128000,
+    "eos_token_id": 128001,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 14336,
+    "max_position_embeddings": 131072,
+    "mlp_bias": false,
+    "model_type": "llama",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 8,
+    "pad_token_id": 128004,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": {
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+        "high_freq_factor": 4.0,
+        "low_freq_factor": 1.0,
+        "original_max_position_embeddings": 8192,
+        "rope_type": "llama3"
+    },
+    "rope_theta": 500000.0,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.55.2",
+    "unsloth_version": "2025.8.5",
+    "use_cache": true,
+    "vocab_size": 128256
+}

generation_config.json

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+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "max_length": 131072,
+  "pad_token_id": 128004,
+  "transformers_version": "4.55.2"
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