README.md

---
license: apache-2.0
---

# Kexer models

Kexer models is a collection of fine-tuned open-source generative text models fine-tuned on Kotlin Exercices dataset. 
This is a repository for fine-tuned CodeLlama-7b model in the Hugging Face Transformers format.

# Model use

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load pre-trained model and tokenizer
model_name = 'JetBrains/CodeLlama-7B-Kexer'
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name).to('cuda')

# Create and encode input
input_text = """\
This function takes an integer n and returns factorial of a number:
fun factorial(n: Int): Int {\
"""
input_ids = tokenizer.encode(
    input_text, return_tensors='pt'
).to('cuda')

# Generate
output = model.generate(
    input_ids, max_length=150, num_return_sequences=1, 
    no_repeat_ngram_size=2, early_stopping=True
)

# Decode output
generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
print(generated_text)
```

# Training setup

The model was trained on one A100 GPU with following hyperparameters:

|         **Hyperparameter**           |             **Value**              |
|:---------------------------:|:----------------------------------------:|
|           `warmup`            |           10%            |
|        `max_lr`        |          1e-4          |
|        `scheduler`        |          linear          |
|        `total_batch_size`        |          256 (~130K tokens per step)          |


# Fine-tuning data

For this model we used 15K exmaples of Kotlin Exercices dataset {TODO: link!}. For more information about the dataset follow th link.

# Evaluation 

To evaluate we used Kotlin Humaneval (more infromation here)

Fine-tuned model:

|         **Model name**           |             **Kotlin HumanEval Pass Rate**              |             **Kotlin Completion**              |
|:---------------------------:|:----------------------------------------:|:----------------------------------------:|
|           `base model`            |           26.89            |           0.388            |
|        `fine-tuned model`        |          42.24         |          0.344          |