gemma
Open weights LLM from Google DeepMind. (by google-deepmind)
gemma_pytorch
The official PyTorch implementation of Google's Gemma models (by google)
gemma | gemma_pytorch | |
---|---|---|
3 | 6 | |
2,080 | 5,059 | |
10.1% | 3.6% | |
5.6 | 7.7 | |
4 days ago | about 1 month ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
gemma
Posts with mentions or reviews of gemma.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-28.
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What are LLMs? An intro into AI, models, tokens, parameters, weights, quantization and more
Medium models: Roughly between 1B to 10B parameters. This is where Mistral 7B, Phi-3, Gemma from Google DeepMind, and wizardlm2 sit. Fun fact: GPT 2 was a medium sized model, much smaller than its latest versions.
- Gemma – a family of lightweight, state-of-the art open models from Google
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Gemma: New Open Models
We've documented the architecture (including key differences) in our technical report here (https://goo.gle/GemmaReport), and you can see the architecture implementation in our Git Repo (https://github.com/google-deepmind/gemma).
gemma_pytorch
Posts with mentions or reviews of gemma_pytorch.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-15.
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Getting Started with Gemma Models
Gemma is a family of lightweight, open-source machine learning models developed by Google AI. These models are designed to be accessible and efficient, making AI development more available for a broad range of users. Released on February 21st, 2024, Gemma is built from the same research and technology that was used to create the Gemini models. Amongst the key features, which are being lightweight and open-source, Gemma is also text-based. It excels in tasks like text summarization, question answering, and reasoning.
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Gemma doesn't suck anymore – 8 bug fixes
Here are the missing links:
* Gemma, a family of open models from Google: https://ai.google.dev/gemma
* Unsloth is a tool/method for training models faster (IIUC): https://github.com/unslothai/unsloth
- The official PyTorch implementation of Google's Gemma models
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Gemma: New Open Models
The release page has comparisons to Mistral everywhere: https://ai.google.dev/gemma
What are some alternatives?
When comparing gemma and gemma_pytorch you can also consider the following projects:
gemma.cpp - lightweight, standalone C++ inference engine for Google's Gemma models.
llama.cpp - LLM inference in C/C++
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
text-to-text-transfer-transformer - Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"
ai-on-gke