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---
base_model: Tesslate/Tessa-T1-32B
tags:
- text-generation-inference
- transformers
- qwen2
- trl
- mlx
license: apache-2.0
language:
- en
datasets:
- Tesslate/Tessa-T1-Dataset
pipeline_tag: text-generation
library_name: mlx
---
# mlx-community/Tessa-T1-32B-mlx-4bit
This model [mlx-community/Tessa-T1-32B-mlx-4bit](https://huggingface.co/mlx-community/Tessa-T1-32B-mlx-4bit) was
converted to MLX format from [Tesslate/Tessa-T1-32B](https://huggingface.co/Tesslate/Tessa-T1-32B)
using mlx-lm version **0.22.2**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Tessa-T1-32B-mlx-4bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
```
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