| base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 | |
| datasets: | |
| - cerebras/SlimPajama-627B | |
| - bigcode/starcoderdata | |
| - HuggingFaceH4/ultrachat_200k | |
| - HuggingFaceH4/ultrafeedback_binarized | |
| language: | |
| - en | |
| license: apache-2.0 | |
| tags: | |
| - mlx | |
| widget: | |
| - example_title: Fibonacci (Python) | |
| messages: | |
| - role: system | |
| content: You are a chatbot who can help code! | |
| - role: user | |
| content: Write me a function to calculate the first 10 digits of the fibonacci | |
| sequence in Python and print it out to the CLI. | |
| # reach-vb/test-mlx-repo | |
| The Model [reach-vb/test-mlx-repo](https://huggingface.co/reach-vb/test-mlx-repo) 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 **0.19.0**. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("reach-vb/test-mlx-repo") | |
| prompt="hello" | |
| if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None: | |
| messages = [{"role": "user", "content": prompt}] | |
| prompt = tokenizer.apply_chat_template( | |
| messages, tokenize=False, add_generation_prompt=True | |
| ) | |
| response = generate(model, tokenizer, prompt=prompt, verbose=True) | |
| ``` | |