Defne-llama3.1-8B

1.0K
6
8.0B
6 languages
llama
by
Eurdem
Language Model
OTHER
8B params
New
1K downloads
Early-stage
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Edge AI:
Mobile
Laptop
Server
18GB+ RAM
Mobile
Laptop
Server
Quick Summary

License: llama3.1, Language: English.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
8GB+ RAM

Training Data Analysis

🟡 Average (4.8/10)

Researched training datasets used by Defne-llama3.1-8B with quality assessment

Specialized For

general
science
multilingual
reasoning

Training Datasets (4)

common crawl
🔴 2.5/10
general
science
Key Strengths
  • •Scale and Accessibility: At 9.5+ petabytes, Common Crawl provides unprecedented scale for training d...
  • •Diversity: The dataset captures billions of web pages across multiple domains and content types, ena...
  • •Comprehensive Coverage: Despite limitations, Common Crawl attempts to represent the broader web acro...
Considerations
  • •Biased Coverage: The crawling process prioritizes frequently linked domains, making content from dig...
  • •Large-Scale Problematic Content: Contains significant amounts of hate speech, pornography, violent c...
c4
🔵 6/10
general
multilingual
Key Strengths
  • •Scale and Accessibility: 750GB of publicly available, filtered text
  • •Systematic Filtering: Documented heuristics enable reproducibility
  • •Language Diversity: Despite English-only, captures diverse writing styles
Considerations
  • •English-Only: Limits multilingual applications
  • •Filtering Limitations: Offensive content and low-quality text remain despite filtering
wikipedia
🟡 5/10
science
multilingual
Key Strengths
  • •High-Quality Content: Wikipedia articles are subject to community review, fact-checking, and citatio...
  • •Multilingual Coverage: Available in 300+ languages, enabling training of models that understand and ...
  • •Structured Knowledge: Articles follow consistent formatting with clear sections, allowing models to ...
Considerations
  • •Language Inequality: Low-resource language editions have significantly lower quality, fewer articles...
  • •Biased Coverage: Reflects biases in contributor demographics; topics related to Western culture and ...
arxiv
🟡 5.5/10
science
reasoning
Key Strengths
  • •Scientific Authority: Peer-reviewed content from established repository
  • •Domain-Specific: Specialized vocabulary and concepts
  • •Mathematical Content: Includes complex equations and notation
Considerations
  • •Specialized: Primarily technical and mathematical content
  • •English-Heavy: Predominantly English-language papers

Explore our comprehensive training dataset analysis

View All Datasets

Code Examples

💻 Kullanım/How to Usepythontransformers
!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"])
💻 Kullanım/How to Usepythontransformers
!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"])
💻 Kullanım/How to Usepythontransformers
!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"])
💻 Kullanım/How to Usepythontransformers
!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"])
💻 Kullanım/How to Usepythontransformers
!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"])
💻 Kullanım/How to Usepythontransformers
!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"])
💻 Kullanım/How to Usepythontransformers
!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"])
💻 Kullanım/How to Usepythontransformers
!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"])

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