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---
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)
```
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