%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
Mobilellm 350M
Overview :
MobileLLM-350M is an autoregressive language model developed by Meta, utilizing an optimized Transformer architecture tailored for device-side applications to meet the needs of resource-constrained environments. The model integrates key technologies such as SwiGLU activation function, deep thin architecture, embedding sharing, and grouped query attention, resulting in significant accuracy improvements in zero-shot commonsense reasoning tasks. MobileLLM-350M offers performance comparable to larger models while maintaining a small model size, making it an ideal choice for natural language processing applications on devices.
Target Users :
The target audience includes researchers and developers in the field of natural language processing, particularly professionals who need to deploy language models on resource-constrained devices. The optimized design of MobileLLM-350M makes it highly suitable for efficient language understanding and generation tasks on mobile devices or embedded systems.
Use Cases
Implementing chatbot functionality on mobile devices for a smooth conversational experience.
Used in smart assistants to provide text-based interactions and information retrieval services.
Integrating into smart home devices for voice control and automated task management.
Features
- Optimized Transformer architecture: An efficient model architecture designed for device-side applications.
- Integration of multiple key technologies: Including SwiGLU activation function, deep thin architecture, embedding sharing, and grouped query attention.
- Zero-shot commonsense reasoning capability: Demonstrating excellent performance across various commonsense reasoning tasks.
- Multiple model size options: Providing models ranging from 125M to 1.5B parameters to accommodate different application needs.
- Support for Hugging Face platform: Ability to load and use pre-trained models directly on the Hugging Face platform.
- Custom code support: Offering pre-trained code for MobileLLM for easy custom training and evaluation.
- Efficient resource utilization: Optimizing computational resource consumption while maintaining performance.
How to Use
1. Visit the Hugging Face website and navigate to the MobileLLM-350M model page.
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%230080ff;%20}%20%3c/style%3e%3c/defs%3e%3cpath%20class='st0'%20d='M16.2,11.1c.4.5.4,1.2,0,1.8l-4.7,7.1h-3.8l5.3-8L7.6,4h3.8l4.7,7.1Z'/%3e%3c/svg%3e)
2. Use the provided code to load the pre-trained MobileLLM-350M model and tokenizer.
3. Add special tokens as needed, such as eos_token and bos_token.
4. Utilize the model for text generation or other NLP tasks.
5. If custom training is required, download the MobileLLM codebase and follow the instructions for data preprocessing and model training.
6. Use evaluation scripts to compute model performance on specific datasets, such as perplexity on the wikitext-2 test set.
7. Integrate the model into your application to implement natural language processing capabilities on devices as per project requirements.
Featured AI Tools
Gemini
Gemini is the latest generation of AI system developed by Google DeepMind. It excels in multimodal reasoning, enabling seamless interaction between text, images, videos, audio, and code. Gemini surpasses previous models in language understanding, reasoning, mathematics, programming, and other fields, becoming one of the most powerful AI systems to date. It comes in three different scales to meet various needs from edge computing to cloud computing. Gemini can be widely applied in creative design, writing assistance, question answering, code generation, and more.
AI Model
11.4M
Chinese Picks
Liblibai
LiblibAI is a leading Chinese AI creative platform offering powerful AI creative tools to help creators bring their imagination to life. The platform provides a vast library of free AI creative models, allowing users to search and utilize these models for image, text, and audio creations. Users can also train their own AI models on the platform. Focused on the diverse needs of creators, LiblibAI is committed to creating inclusive conditions and serving the creative industry, ensuring that everyone can enjoy the joy of creation.
AI Model
6.9M