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RichardErkhov/Eurdem_-_Defne-llama3.1-8B-gguf
Eurdem_-_Defne-llama3.1-8B-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
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.gguf108 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
Defne-llama3.1-8B - GGUF
| 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 |
license: llama3.1 language:
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.
!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"])
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.
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.