TheBlueObserver commited on
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06a5d3b94fb688e27467ec1f30522a5b9f7c8cc863dce0a990940efefdabce07

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README.md ADDED
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+ ---
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+ base_model: HuggingFaceTB/SmolLM2-360M-Instruct
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+ language:
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+ - en
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+ library_name: transformers
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+ license: apache-2.0
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+ pipeline_tag: text-generation
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+ tags:
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+ - safetensors
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+ - onnx
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+ - transformers.js
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+ - mlx
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+ ---
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+
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+ # TheBlueObserver/SmolLM2-360M-Instruct-MLX
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+
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+ The Model [TheBlueObserver/SmolLM2-360M-Instruct-MLX](https://huggingface.co/TheBlueObserver/SmolLM2-360M-Instruct-MLX) was
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+ converted to MLX format from [HuggingFaceTB/SmolLM2-360M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct)
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+ using mlx-lm version **0.20.2**.
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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("TheBlueObserver/SmolLM2-360M-Instruct-MLX")
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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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+ {
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "is_llama_config": true,
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+ "max_position_embeddings": 8192,
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+ "mlp_bias": false,
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+ "model_type": "llama",
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+ "num_attention_heads": 15,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 5,
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+ "pad_token_id": 2,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_interleaved": false,
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+ "rope_scaling": null,
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+ "rope_theta": 100000,
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+ "tie_word_embeddings": true,
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+ "torch_dtype": "bfloat16",
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+ "transformers.js_config": {
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+ "kv_cache_dtype": {
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+ "q4f16": "float16",
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+ "fp16": "float16"
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+ }
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+ },
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+ "transformers_version": "4.42.3",
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+ "use_cache": true,
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+ "vocab_size": 49152
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+ }
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