README.md

---
datasets:
- arbml/CIDAR
base_model: google/gemma-2b-it
pipeline_tag: text-generation
language:
- ar
- en
---

# Fine-Tuning-Gemma-2b-it-for-Arabic

<!-- Provide a quick summary of what the model is/does. -->
This model is a fine-tuned version of [google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it) on [arbml/CIDAR](https://huggingface.co/datasets/arbml/CIDAR) Arabic dataset.  

It achieves the following results on the evaluation set:
- training_loss=2.281057505607605



### Direct Use

<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Ruqiya/Fine-Tuning-Gemma-2b-it-for-Arabic"
messages = [{"role": "user", "content": "ما هو الذكاء الاصطناعي؟"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```