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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,40 @@
+---
+base_model: pfnet/Preferred-MedLLM-Qwen-72B
+language:
+- en
+- ja
+library_name: transformers
+pipeline_tag: text-generation
+license: other
+license_name: qwen
+tags:
+- mlx
+---
+
+# mlx-community/Preferred-MedLLM-Qwen-72B-8bit
+
+The Model [mlx-community/Preferred-MedLLM-Qwen-72B-8bit](https://huggingface.co/mlx-community/Preferred-MedLLM-Qwen-72B-8bit) was
+converted to MLX format from [pfnet/Preferred-MedLLM-Qwen-72B](https://huggingface.co/pfnet/Preferred-MedLLM-Qwen-72B)
+using mlx-lm version **0.21.5**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("mlx-community/Preferred-MedLLM-Qwen-72B-8bit")
+
+prompt = "hello"
+
+if tokenizer.chat_template is not None:
+    messages = [{"role": "user", "content": prompt}]
+    prompt = tokenizer.apply_chat_template(
+        messages, add_generation_prompt=True
+    )
+
+response = generate(model, tokenizer, prompt=prompt, verbose=True)
+```

added_tokens.json

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+}

config.json

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+        "Qwen2ForCausalLM"
+    ],
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+    "initializer_range": 0.02,
+    "intermediate_size": 29568,
+    "max_position_embeddings": 131072,
+    "max_window_layers": 80,
+    "model_type": "qwen2",
+    "num_attention_heads": 64,
+    "num_hidden_layers": 80,
+    "num_key_value_heads": 8,
+    "quantization": {
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+        "bits": 8
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+    "rope_theta": 1000000.0,
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+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.49.0",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 152064
+}

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special_tokens_map.json

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tokenizer_config.json

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