---
base_model: Doctor-Shotgun/TinyLlama-1.1B-32k-Instruct
datasets:
- LDJnr/Capybara
- jondurbin/airoboros-3.2
- unalignment/toxic-dpo-v0.1
- LDJnr/Verified-Camel
- HuggingFaceH4/no_robots
- Doctor-Shotgun/no-robots-sharegpt
- Doctor-Shotgun/capybara-sharegpt
language:
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- llama
- mlx
inference: false
---

# vrglx33/TinyLlama-1.1B-32k-Instruct-mlx

The Model [vrglx33/TinyLlama-1.1B-32k-Instruct-mlx](https://huggingface.co/vrglx33/TinyLlama-1.1B-32k-Instruct-mlx) was converted to MLX format from [Doctor-Shotgun/TinyLlama-1.1B-32k-Instruct](https://huggingface.co/Doctor-Shotgun/TinyLlama-1.1B-32k-Instruct) using mlx-lm version **0.19.3**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("vrglx33/TinyLlama-1.1B-32k-Instruct-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)
```