---
license: apache-2.0
library_name: peft
tags:
- code
datasets:
- mlabonne/CodeLlama-2-20k
base_model: meta-llama/Llama-2-7b-hf
---

# 🦙💻 CodeLlama 

📝 [Article](https://towardsdatascience.com/fine-tune-your-own-llama-2-model-in-a-colab-notebook-df9823a04a32) |
💻 [Colab](https://colab.research.google.com/drive/1PEQyJO1-f6j0S_XJ8DV50NkpzasXkrzd?usp=sharing) |
📄 [Script](https://gist.github.com/mlabonne/b5718e1b229ce6553564e3f56df72c5c)

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

`CodeLlama-7b` is a Llama 2 version of [**CodeAlpaca**](https://github.com/sahil280114/codealpaca).

## 🔧 Training

This model is based on the `llama-2-7b-chat-hf` model, fine-tuned using QLoRA on the [`mlabonne/CodeLlama-2-20k`](https://huggingface.co/datasets/mlabonne/CodeLlama-2-20k) dataset. It was trained on an RTX 3090 and can be used for inference.

It was trained using this custom [`finetune_llama2.py`](https://gist.github.com/mlabonne/b5718e1b229ce6553564e3f56df72c5c) script as follows:

``` bash
python finetune_llama2.py --dataset_name=mlabonne/CodeLlama-2-20k --new_model=mlabonne/codellama-2-7b --bf16=True --learning_rate=2e-5
```

<center><img src="https://i.imgur.com/5Qx7Kzo.png"></center>

## 💻 Usage

``` python
# pip install transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mlabonne/codellama-2-7b"
prompt = "Write Python code to generate an array with all the numbers from 1 to 100"

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']}")
```

Ouput:
```
Here is a Python code to generate an array with all the numbers from 1 to 100:

 ```
 numbers = []
 for i in range(1,101):
     numbers.append(i)
 ```

This code generates an array with all the numbers from 1 to 100 in Python. It uses a loop that iterates over the range of numbers from 1 to 100, and for each number, it appends that number to the array 'numbers'. The variable 'numbers' is initialized to a list, and its length is set to 101 by using the range of numbers (0-99).

```## Training procedure


The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions

- PEFT 0.5.0.dev0

- PEFT 0.5.0.dev0
## Training procedure


The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16