---
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/TinyLlama-1.1B-Chat-v1.0-Q4-mlx

The Model [reach-vb/TinyLlama-1.1B-Chat-v1.0-Q4-mlx](https://huggingface.co./reach-vb/TinyLlama-1.1B-Chat-v1.0-Q4-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**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("reach-vb/TinyLlama-1.1B-Chat-v1.0-Q4-mlx")

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)
```