Today's LLM & Language Models: Fastest-Growing Projects — April 26, 2026
Today's the LLM & Language Models space, we're seeing a surge of interest in tools that enhance the functionality and usability of large language models. Many repositories are focusing on developing personal knowledge bases, improving model interpretability, and increasing accessibility to these powerful AI tools.
OpenAI's Privacy Filter has taken the top spot with an impressive Growth Score of 99.78 and over 1,430 stars. This tool allows for the detection and masking of personally identifiable information (PII) in text data, making it a crucial component in ensuring user privacy when working with LLMs. Its growth can be attributed to its importance in real-world applications where sensitive data is involved.
Arman-bd's GuppyLM has gained significant traction with 3,015 stars and a Growth Score of 69.80. This ~9M parameter language model is designed to mimic the conversational style of a small fish, showcasing the creative possibilities within the realm of LLMs. Its growth likely stems from its unique persona and the expanding interest in more specialized models that can cater to specific use cases.
Chiefautism's Privacy Parser has seen notable growth with 319 stars and a Growth Score of 68.67. This tool offers an alternative approach to OpenAI's Privacy Filter by returning PII as structured spans instead of masking them, allowing for more nuanced handling of sensitive information. Its growth is likely driven by the need for flexible solutions in data processing workflows.
Hexiecs' Talk Normal has garnered attention with 1,497 stars and a Growth Score of 55.33. This system prompt aims to make any LLM communicate like a normal person by removing AI-specific linguistic patterns. Its popularity can be attributed to its ability to enhance user experience when interacting with language models.
Sdyckjq-lab's llm-wiki-skill has achieved a respectable Growth Score of 52.10 and gathered over 1,108 stars. This tool enables the construction of personal knowledge bases using Karpathy's LLM Wiki methodology, providing users with an organized repository of information. Its growth likely stems from its potential to aid in research, education, and personal knowledge management.
Amitshekhariitbhu's llm-internals has earned 634 stars and a Growth Score of 31.11. This educational resource provides step-by-step explanations on the inner workings of LLMs, covering topics from tokenization to inference optimization. Its growth can be attributed to its value in educating developers and researchers about the intricacies of these models.
Kessler's Gemma-Gem has attracted interest with 839 stars and a Growth Score of 29.48. This project enables on-device execution of Google's Gemma 4 model using WebGPU, eliminating the need for API keys or cloud services. Its growth likely stems from its innovative approach to model deployment and data security.
Xoai's sage-wiki has seen notable activity with 465 stars and a Growth Score of 29.45. This tool compiles personal knowledge bases by extracting concepts, discovering cross-references, and creating a searchable wiki. Its growth is likely driven by the expanding need for effective knowledge organization tools.
Atomicmemory's llm-wiki-compiler has gathered attention with 776 stars and a Growth Score of 29.05. This knowledge compiler transforms raw sources into interlinked wikis, inspired by Karpathy's LLM Wiki pattern. Its popularity can be attributed to its ability to streamline the process of creating personal knowledge bases.
Lucasastorian's llmwiki has earned 677 stars and a Growth Score of 28.07. This open-source implementation of Karpathy's LLM Wiki enables users to upload documents, connect their Claude account via MCP, and generate a wiki. Its growth likely stems from its ease of use and integration with popular services.
OpenAI's Privacy Filter has taken the top spot with an impressive Growth Score of 99.78 and over 1,430 stars. This tool allows for the detection and masking of personally identifiable information (PII) in text data, making it a crucial component in ensuring user privacy when working with LLMs. Its growth can be attributed to its importance in real-world applications where sensitive data is involved.
Arman-bd's GuppyLM has gained significant traction with 3,015 stars and a Growth Score of 69.80. This ~9M parameter language model is designed to mimic the conversational style of a small fish, showcasing the creative possibilities within the realm of LLMs. Its growth likely stems from its unique persona and the expanding interest in more specialized models that can cater to specific use cases.
Chiefautism's Privacy Parser has seen notable growth with 319 stars and a Growth Score of 68.67. This tool offers an alternative approach to OpenAI's Privacy Filter by returning PII as structured spans instead of masking them, allowing for more nuanced handling of sensitive information. Its growth is likely driven by the need for flexible solutions in data processing workflows.
Hexiecs' Talk Normal has garnered attention with 1,497 stars and a Growth Score of 55.33. This system prompt aims to make any LLM communicate like a normal person by removing AI-specific linguistic patterns. Its popularity can be attributed to its ability to enhance user experience when interacting with language models.
Sdyckjq-lab's llm-wiki-skill has achieved a respectable Growth Score of 52.10 and gathered over 1,108 stars. This tool enables the construction of personal knowledge bases using Karpathy's LLM Wiki methodology, providing users with an organized repository of information. Its growth likely stems from its potential to aid in research, education, and personal knowledge management.
Amitshekhariitbhu's llm-internals has earned 634 stars and a Growth Score of 31.11. This educational resource provides step-by-step explanations on the inner workings of LLMs, covering topics from tokenization to inference optimization. Its growth can be attributed to its value in educating developers and researchers about the intricacies of these models.
Kessler's Gemma-Gem has attracted interest with 839 stars and a Growth Score of 29.48. This project enables on-device execution of Google's Gemma 4 model using WebGPU, eliminating the need for API keys or cloud services. Its growth likely stems from its innovative approach to model deployment and data security.
Xoai's sage-wiki has seen notable activity with 465 stars and a Growth Score of 29.45. This tool compiles personal knowledge bases by extracting concepts, discovering cross-references, and creating a searchable wiki. Its growth is likely driven by the expanding need for effective knowledge organization tools.
Atomicmemory's llm-wiki-compiler has gathered attention with 776 stars and a Growth Score of 29.05. This knowledge compiler transforms raw sources into interlinked wikis, inspired by Karpathy's LLM Wiki pattern. Its popularity can be attributed to its ability to streamline the process of creating personal knowledge bases.
Lucasastorian's llmwiki has earned 677 stars and a Growth Score of 28.07. This open-source implementation of Karpathy's LLM Wiki enables users to upload documents, connect their Claude account via MCP, and generate a wiki. Its growth likely stems from its ease of use and integration with popular services.