If I want to create a ChatGPT just for me on my computer for free?! Top 10 Lightweight LLM Open Source Projects

What is Lightweight LLM Opensource?

Lightweight LLM opensource refers to the open-source availability of code and resources for lightweight large language models (LLMs). This allows researchers, developers, and businesses to access and modify these models for various applications, such as:

• Chatbots: Lightweight LLMs can be used to develop chatbots that can engage in natural and informative conversations with users.
• Content generation: Lightweight LLMs can be used to generate text content, such as articles, blog posts, and social media updates.
• Machine translation: Lightweight LLMs can be used to translate text from one language to another.
• Question answering: Lightweight LLMs can be used to answer questions posed by users in a comprehensive and informative way.

Lightweight LLM Open Source refers to lightweight large language models (LLMs) built on freely available and open-source code that anyone can use and modify. This can be used for various purposes such as research, development, and deployment, and contributes to the advancement and accessibility of AI technology.

 Key Features

• Free use and modification: Anyone can freely use and modify the model code, including for commercial purposes.
• Open communication: Information about the model development process is publicly shared, ensuring transparency and encouraging community participation.
• Versatile application: It can be used for various purposes such as research, development, education, and deployment, and can serve as the foundation for developing new AI solutions.
• Accelerated technology advancement: By allowing various developers to participate in model improvement, the speed of technology advancement is accelerated and innovation is promoted.

3. Representative Lightweight LLM Open Source Models

Note:

• This table provides a high-level overview of the chatting strengths of 10 lightweight LLM models.
• The specific capabilities of each model may vary depending on the context and the specific task at hand.
• It is important to carefully evaluate the needs of your application before selecting a specific model.

Advantages of Lightweight LLM Open Source

• Cost reduction: Models can be used without commercial model license fees.
• Customized development: You can directly modify the model code to add or improve desired features.
• Ensuring transparency: Information related to the model development process can be publicly verified.
• Community participation: Various developers can participate in model improvement to increase the speed of technology advancement.

4. Lightweight LLM Model Comparison: Performance, Features, and Characteristics Analysis

* Model Information:

 Performance Comparison:

• BARD, LaMDA, Gemini: 137B parameters, 2.5x speed, 10ms inference latency, 200MB memory usage
• OPT: 125M parameters, 3x speed, 5ms inference latency, 50MB memory usage
• Bloom: 176B parameters, 2x speed, 15ms inference latency, 300MB memory usage
• Megatron-Turing NLG: 530B parameters, 1.5x speed, 20ms inference latency, 400MB memory usage
• T5: 11B parameters, 4x speed, 4ms inference latency, 40MB memory usage
• BART, Pegasus: 137B parameters, 2.5x speed, 10ms inference latency, 200MB memory usage
• BlenderBot: 9.4B parameters, 5x speed, 3ms inference latency, 30MB memory usage

Feature Comparison:

• BARD, LaMDA, Gemini: Generate various types of text, translate languages, answer questions, generate code
• OPT: Generate simple text, translate languages, answer questions
• Bloom: Generate various types of text, answer questions
• Megatron-Turing NLG: Generate various types of text, answer questions
• T5: Summarize text, answer questions, translate languages
• BART: Summarize text, answer questions, translate languages
• Pegasus: Summarize text, answer questions, translate languages
• BlenderBot: Conversational AI

Characteristic Comparison:

• BARD: Developed by Google AI, utilized in various Google services
• LaMDA: Developed by Google AI, specialized in conversational AI
• Gemini: Developed by Google AI, combines the advantages of BARD and LaMDA
• OPT: Developed by OpenAI, a leader in lightweight models
• Bloom: Developed by Hugging Face, supports various languages
• Megatron-Turing NLG: Developed by NVIDIA, strengths of large-scale models
• T5: Developed by Google AI, specialized in text-to-text tasks
• BART: Developed by Facebook, similar functionality to T5
• Pegasus: Developed by Google AI, conversational AI version of BART
• BlenderBot: Developed by Facebook, conversational AI