gemma-1.1-2b-it
Maintainer: google
93
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The gemma-1.1-2b-it is an instruction-tuned version of the Gemma 2B language model from Google. It is part of the Gemma family of lightweight, state-of-the-art open models built using the same research and technology as Google's Gemini models. Gemma models are text-to-text, decoder-only large language models available in English, with open weights, pre-trained variants, and instruction-tuned variants. The 2B and 7B variants of the Gemma models offer different size and performance trade-offs, with the 2B model being more efficient and the 7B model providing higher performance.
Model inputs and outputs
Inputs
- Text string: The model can take a variety of text inputs, such as a question, a prompt, or a document to be summarized.
Outputs
- Generated English-language text: The model produces text in response to the input, such as an answer to a question or a summary of a document.
Capabilities
The gemma-1.1-2b-it model is capable of a wide range of text generation tasks, including question answering, summarization, and reasoning. It can be used to generate creative text formats like poems, scripts, code, marketing copy, and email drafts. The model can also power conversational interfaces for customer service, virtual assistants, or interactive applications.
What can I use it for?
The Gemma family of models is well-suited for a variety of natural language processing and generation tasks. The instruction-tuned variants like gemma-1.1-2b-it can be particularly useful for applications that require following specific instructions or engaging in multi-turn conversations.
Some potential use cases include:
- Content Creation: Generate text for marketing materials, scripts, emails, or creative writing.
- Chatbots and Conversational AI: Power conversational interfaces for customer service, virtual assistants, or interactive applications.
- Text Summarization: Produce concise summaries of large text corpora, research papers, or reports.
- Research and Education: Serve as a foundation for NLP research, language learning tools, or knowledge exploration.
Things to try
One key capability of the gemma-1.1-2b-it model is its ability to engage in coherent, multi-turn conversations. By using the provided chat template, you can prompt the model to maintain context and respond appropriately to a series of user inputs, rather than generating isolated responses. This makes the model well-suited for conversational applications, where maintaining context and following instructions is important.
Another interesting aspect of the Gemma models is their relatively small size compared to other large language models. This makes them more accessible to deploy in resource-constrained environments like laptops or personal cloud infrastructure, democratizing access to state-of-the-art AI technology.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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