RichardErkhov/Eurdem_-_Defne-llama3.1-8B-gguf

Quantization made by Richard Erkhov.

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Defne-llama3.1-8B - GGUF

• Model creator: https://huggingface.co/Eurdem/
• Original model: https://huggingface.co/Eurdem/Defne-llama3.1-8B/

Name	Quant method	Size
Defne-llama3.1-8B.Q2_K.gguf	Q2_K	2.96GB
Defne-llama3.1-8B.IQ3_XS.gguf	IQ3_XS	3.28GB
Defne-llama3.1-8B.IQ3_S.gguf	IQ3_S	3.43GB
Defne-llama3.1-8B.Q3_K_S.gguf	Q3_K_S	3.41GB
Defne-llama3.1-8B.IQ3_M.gguf	IQ3_M	3.52GB
Defne-llama3.1-8B.Q3_K.gguf	Q3_K	3.74GB
Defne-llama3.1-8B.Q3_K_M.gguf	Q3_K_M	3.74GB
Defne-llama3.1-8B.Q3_K_L.gguf	Q3_K_L	4.03GB
Defne-llama3.1-8B.IQ4_XS.gguf	IQ4_XS	4.18GB
Defne-llama3.1-8B.Q4_0.gguf	Q4_0	4.34GB
Defne-llama3.1-8B.IQ4_NL.gguf	IQ4_NL	4.38GB
Defne-llama3.1-8B.Q4_K_S.gguf	Q4_K_S	4.37GB
Defne-llama3.1-8B.Q4_K.gguf	Q4_K	4.58GB
Defne-llama3.1-8B.Q4_K_M.gguf	Q4_K_M	4.58GB
Defne-llama3.1-8B.Q4_1.gguf	Q4_1	4.78GB
Defne-llama3.1-8B.Q5_0.gguf	Q5_0	5.21GB
Defne-llama3.1-8B.Q5_K_S.gguf	Q5_K_S	5.21GB
Defne-llama3.1-8B.Q5_K.gguf	Q5_K	5.34GB
Defne-llama3.1-8B.Q5_K_M.gguf	Q5_K_M	5.34GB
Defne-llama3.1-8B.Q5_1.gguf	Q5_1	5.65GB
Defne-llama3.1-8B.Q6_K.gguf	Q6_K	6.14GB
Defne-llama3.1-8B.Q8_0.gguf	Q8_0	7.95GB

Original model description:

license: llama3.1 language: - en - tr - de - fr - it - es library_name: transformers pipeline_tag: text-generation tags: - llama-3 - safetensors

Fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct, trained on Turkish dataset (~4 mio tokens). Then it is merged with VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct.

💻 Kullanım/How to Use

!pip install -qU transformers bitsandbytes accelerate

import transformers
import torch

model_id = "Eurdem/Defne-llama3.1-8B"

pipeline = transformers.pipeline(
                                "text-generation",
                                model=model_id,
                                model_kwargs={"torch_dtype": torch.bfloat16, "load_in_8bit": True},
                                device_map="auto",
                                )

## For English
messages = [{"role": "system", "content": "You are a helpful chatbot, named Defne, who always responds friendly."},
            {"role": "user", "content": "Answer the questions: 1) Who are you? 2) f(x)=3x^2+4x+12 so what is f(3)?"},
]

## For Turkish
messages = [{"role": "system", "content": "Sen, Defne isimli Türkçe konuşan bir chatbotsun."},
            {"role": "user", "content": "Soruları numaralandırarak cevapla. 1) Sen kimsin?  2) f(x)=3x^2+4x+12 ise f(3) kaçtır?"}
]

outputs = pipeline(
                  messages,
                  max_new_tokens=1024,
                  do_sample=True,
                  temperature=0.5,
                  top_p=0.5,
                  top_k=100,
                )

print(outputs[0]["generated_text"][-1]["content"])

English Output

Hello there! I'm Defne, a friendly chatbot here to help you with any questions or tasks you might have.

Now, let's answer your questions:

1. I am Defne, a helpful chatbot designed to provide friendly and informative responses to your queries. I'm always happy to assist you with anything you need help with!

2. To find f(3) for the given function f(x) = 3x^2 + 4x + 12, we simply need to substitute x with 3 in the function.

f(3) = 3(3)^2 + 4(3) + 12
     = 3(9) + 12 + 12
     = 27 + 12 + 12
     = 51

So, f(3) equals 51.

Türkçe Çıktı

1) Ben Defne, Türkçe konuşan bir chatbotum. İnsanlarla sohbet etmek ve onlara yardımcı olmak için tasarlanmış bir yapay zekâ uygulamasıyım.

2) f(x) = 3x^2 + 4x + 12 formülüne x = 3 değerini koyarsak:
f(3) = 3(3)^2 + 4(3) + 12
f(3) = 3(9) + 12 + 12
f(3) = 27 + 12 + 12
f(3) = 51
Sonuç olarak, f(3) = 51'dir.