Introduction

Gemini Pro is a state-of-the-art large language model (LLM) developed by Google DeepMind. This model represents a significant step forward in the field of artificial intelligence, offering multimodal capabilities and advanced reasoning for a wide range of tasks. 

Gemini Pro Model

Gemini Pro is a Gemini large language model that understands and generates language. It's a foundation model that performs well at a variety of natural language tasks such as summarization, instruction following, content generation, sentiment analysis, entity extraction, classification etc. The type of content that Gemini Pro can create includes document summaries, answers to questions, labels that classify content, and more.

Run Gemini Pro with an API

Running the API with Clarifai's Python SDK

You can run the Gemini Pro Model API using Clarifai’s Python SDK.

Export your PAT as an environment variable. Then, import and initialize the API Client.

Find your PAT in your security settings.

export CLARIFAI_PAT={your personal access token}

from clarifai.client.model import Model

prompt = "what will be the future of AI?"

api_key = API_KEY

inference_params = dict(temperature=0.2, top_k =50, top_p=0.95, max_tokens=100, api_key = api_key)

# Model Predict
model_prediction = Model("https://clarifai.com/gcp/generate/models/gemini-pro").predict_by_bytes(prompt.encode(), input_type="text", inference_params=inference_params)

print(model_prediction.outputs[0].data.text.raw)

You can also run Gemini Pro API using other Clarifai Client Libraries like Java, cURL, NodeJS, PHP, etc here.

Use cases

• Summarization: Create a shorter version of a document that incorporates pertinent information from the original text. For example, summarize a chapter from a textbook or create a product description from a longer text.
• Question answering: Provide answers to questions in text. For example, automate the creation of a Frequently Asked Questions (FAQ) document from knowledge base content.
• Classification: Assign a label describing the provided text. For example, apply labels that describe whether a block of text is grammatically correct.
• Sentiment analysis: This is a form of classification that identifies the sentiment of text. The sentiment is turned into a label that's applied to the text. For example, the sentiment of text might be polarities like positive or negative, or sentiments like anger or happiness.
• Entity extraction: Extract a piece of information from text. For example, extract the name of a movie from the text of an article.
• Content creation: Generate texts by specifying a set of requirements and background. For example, draft an email under a given context using a certain tone.

Advantages

• Sophisticated Reasoning: The model's sophisticated reasoning capabilities make it adept at extracting insights from vast amounts of data, contributing to breakthroughs in various fields.
• Advanced Coding: Gemini Pro can understand, explain, and generate high-quality code in popular programming languages, making it a valuable tool for developers and coding competitions.
• Reliable and Efficient: Trained at scale using Google's Tensor Processing Units (TPUs), Gemini Pro is reliable, scalable, and efficient, running significantly faster than earlier models.
• Safety and Responsibility: Gemini Pro undergoes comprehensive safety evaluations, addressing potential risks and incorporating safeguards against biases and toxicity. Google is committed to responsible AI development, collaborating with external experts to ensure ethical use.

Disclaimer

Please be advised that this model utilizes wrapped Artificial Intelligence (AI) provided by GCP (the "Vendor"). These AI models may collect, process, and store data as part of their operations. By using our website and accessing these AI models, you hereby consent to the data practices of the Vendor. We do not have control over the data collection, processing, and storage practices of the Vendor. Therefore, we cannot be held responsible or liable for any data handling practices, data loss, or breaches that may occur. It is your responsibility to review the privacy policies and terms of service of the Vendor to understand their data practices. You can access the Vendor's privacy policy and terms of service at https://cloud.google.com/privacy.

We disclaim all liability with respect to the actions or omissions of the Vendor, and we encourage you to exercise caution and to ensure that you are comfortable with these practices before utilizing the AI models hosted on our site.