---
license: apache-2.0
datasets:
- mlabonne/mini-platypus
pipeline_tag: text-generation
---
# 🦙🧠 Miniplatypus-7b

<center><img src="https://i.imgur.com/VkGvQym.png" width="300"></center>

This is a `Llama-2-7b-chat` model fine-tuned using QLoRA (4-bit precision) on the [`mlabonne/guanaco-llama2-1k`](https://huggingface.co/datasets/mlabonne/mini-platypus) dataset, which is a subset of the [`garage-bAInd/Open-Platypus`](https://huggingface.co/datasets/garage-bAInd/Open-Platypus).

## 🔧 Training

It was trained on a Google Colab notebook with a T4 GPU. It is mainly designed for educational purposes, not for inference.

## 💻 Usage

``` python
# pip install transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mlabonne/llama-2-7b-miniplatypus"
prompt = "What is a large language model?"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

sequences = pipeline(
    f'<s>[INST] {prompt} [/INST]',
    do_sample=True,
    top_k=10,
    num_return_sequences=1,
    eos_token_id=tokenizer.eos_token_id,
    max_length=200,
)
for seq in sequences:
    print(f"Result: {seq['generated_text']}")
```