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mlx-community
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AMD-Llama-135m-code-8bit

MLX
Safetensors
llama
8-bit precision
Model card Files Community
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Goekdeniz-Guelmez commited on
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Files changed (8) hide show
  1. README.md +35 -0
  2. config.json +35 -0
  3. model.safetensors +3 -0
  4. model.safetensors.index.json +290 -0
  5. special_tokens_map.json +23 -0
  6. tokenizer.json +0 -0
  7. tokenizer.model +3 -0
  8. tokenizer_config.json +42 -0
README.md ADDED
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+ ---
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+ base_model: amd/AMD-Llama-135m-code
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+ datasets:
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+ - cerebras/SlimPajama-627B
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+ - manu/project_gutenberg
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+ license: apache-2.0
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+ tags:
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+ - mlx
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+ ---
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+
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+ # mlx-community/AMD-Llama-135m-code-8bit
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+
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+ The Model [mlx-community/AMD-Llama-135m-code-8bit](https://huggingface.co/mlx-community/AMD-Llama-135m-code-8bit) was converted to MLX format from [amd/AMD-Llama-135m-code](https://huggingface.co/amd/AMD-Llama-135m-code) 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/AMD-Llama-135m-code-8bit")
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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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+ ```
config.json ADDED
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+ {
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ "attention_bias": false,
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+ "eos_token_id": 2,
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 2048,
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+ "max_position_embeddings": 2048,
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+ "model_type": "llama",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "num_key_value_heads": 12,
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+ "pretraining_tp": 1,
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+ "quantization": {
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+ "group_size": 64,
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+ "bits": 8
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+ },
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+ "quantization_config": {
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+ "group_size": 64,
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+ "bits": 8
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+ },
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 10000.0,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.36.2",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
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