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e0592a0f09703b76649e3ab193dd35c2caa36b166f44a7090068176385dd194d

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README.md ADDED
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+ ---
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+ base_model: Qwen/Qwen2.5-72B-Instruct
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+ language:
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+ - en
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+ license: other
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+ license_name: qwen
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+ license_link: https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE
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+ pipeline_tag: text-generation
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+ tags:
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+ - chat
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+ - mlx
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+ ---
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+
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+ # mlx-community/Qwen2.5-72B-Instruct-4bit
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+
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+ The Model [mlx-community/Qwen2.5-72B-Instruct-4bit](https://huggingface.co/mlx-community/Qwen2.5-72B-Instruct-4bit) was converted to MLX format from [Qwen/Qwen2.5-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct) using mlx-lm version **0.18.2**.
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+
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+ ## Use with mlx
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+
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+ ```bash
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+ pip install mlx-lm
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+ ```
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("mlx-community/Qwen2.5-72B-Instruct-4bit")
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+
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+ prompt="hello"
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+
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+ if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
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+ messages = [{"role": "user", "content": prompt}]
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+ prompt = tokenizer.apply_chat_template(
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+ messages, tokenize=False, add_generation_prompt=True
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+ )
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+
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+ response = generate(model, tokenizer, prompt=prompt, verbose=True)
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+ ```
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config.json ADDED
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+ {
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+ "architectures": [
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+ "Qwen2ForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 151643,
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+ "hidden_act": "silu",
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+ "hidden_size": 8192,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 29568,
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+ "max_position_embeddings": 32768,
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+ "max_window_layers": 70,
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+ "model_type": "qwen2",
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+ "num_attention_heads": 64,
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+ "num_hidden_layers": 80,
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+ "num_key_value_heads": 8,
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+ "quantization": {
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+ "group_size": 64,
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+ "bits": 4
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+ },
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+ "quantization_config": {
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+ "group_size": 64,
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+ "bits": 4
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+ },
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+ "rms_norm_eps": 1e-06,
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+ "rope_theta": 1000000.0,
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+ "sliding_window": 131072,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.43.1",
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+ "use_cache": true,
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merges.txt ADDED
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tokenizer.json ADDED
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vocab.json ADDED
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