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by pcuenq HF staff - opened
README.md ADDED
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+ ---
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+ base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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+ datasets:
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+ - cerebras/SlimPajama-627B
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+ - bigcode/starcoderdata
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+ - HuggingFaceH4/ultrachat_200k
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+ - HuggingFaceH4/ultrafeedback_binarized
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+ language:
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+ - en
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+ license: apache-2.0
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+ tags:
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+ - mlx
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+ widget:
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+ - example_title: Fibonacci (Python)
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+ messages:
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+ - role: system
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+ content: You are a chatbot who can help code!
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+ - role: user
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+ content: Write me a function to calculate the first 10 digits of the fibonacci
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+ sequence in Python and print it out to the CLI.
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+ ---
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+
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+ # pcuenq/TinyLlama-1.1B-Chat-v1.0-Q8-mlx
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+
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+ The Model [pcuenq/TinyLlama-1.1B-Chat-v1.0-Q8-mlx](https://huggingface.co/pcuenq/TinyLlama-1.1B-Chat-v1.0-Q8-mlx) was converted to MLX format from [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) using mlx-lm version **0.19.1**.
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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("pcuenq/TinyLlama-1.1B-Chat-v1.0-Q8-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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+ "max_position_embeddings": 2048,
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+ "model_type": "llama",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 22,
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+ "num_key_value_heads": 4,
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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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+ },
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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": "bfloat16",
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+ "transformers_version": "4.35.0",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
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