Text Generation
Transformers
Safetensors
MLX
Japanese
qwen2
conversational
text-generation-inference
Inference Endpoints
4-bit precision
File size: 1,080 Bytes
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---
license: apache-2.0
language:
- ja
pipeline_tag: text-generation
library_name: transformers
base_model: SakanaAI/TinySwallow-1.5B-Instruct
datasets:
- tokyotech-llm/lmsys-chat-1m-synth
- tokyotech-llm/swallow-magpie-ultra-v0.1
- tokyotech-llm/swallow-swallow-gemma-magpie-v0.1
tags:
- mlx
---

# mlx-community/TinySwallow-1.5B-Instruct-4bit

The Model [mlx-community/TinySwallow-1.5B-Instruct-4bit](https://huggingface.co./mlx-community/TinySwallow-1.5B-Instruct-4bit) was
converted to MLX format from [SakanaAI/TinySwallow-1.5B-Instruct](https://huggingface.co./SakanaAI/TinySwallow-1.5B-Instruct)
using mlx-lm version **0.21.1**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/TinySwallow-1.5B-Instruct-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)
```