RichardErkhov/Ruqiya_-_Fine-Tuning-Gemma-2b-it-for-Arabic-gguf

Quantization made by Richard Erkhov.

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

• —Model creator: https://huggingface.co/Ruqiya/
• —Original model: https://huggingface.co/Ruqiya/Fine-Tuning-Gemma-2b-it-for-Arabic/

Original model description: --- datasets:

• —arbml/CIDAR basemodel: google/gemma-2b-it pipelinetag: 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 on 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. -->

!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"])