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-4-bit | |
The Model [reach-vb/test-mlx-repo-4-bit](https://huggingface.co/reach-vb/test-mlx-repo-4-bit) 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-4-bit") | |
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) | |
``` | |