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Llama 2 70b

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The llama-2-70b is a language model developed by Meta. It is based on the Llama 2 model and has 70 billion parameters. This language model can generate coherent and contextually relevant text based on given prompts. It is designed to assist in various natural language processing tasks, including text generation, completion, and understanding.

Use cases

The llama-2-70b language model has a wide range of potential use cases in the field of natural language processing. It can be used for text generation, allowing users to create coherent and contextually relevant text based on prompts. This can be helpful in content creation, brainstorming ideas, and even writing assistance. The model can also be employed in text completion tasks, enabling it to generate suggestions and fill in missing information in a given sentence or paragraph. Additionally, the llama-2-70b model can be utilized for text understanding, assisting in tasks such as sentiment analysis, summarization, and question answering. Overall, this language model holds great potential for applications in various domains, including content generation, writing assistance tools, virtual assistants, and automated customer support systems.

Text-to-Text

Pricing

Cost per run
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USD
Avg run time
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Hardware
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Prediction

Creator Models

ModelCostRuns
Elixir Gen$?44
Llama 2 7b$?5,325
Llama 2 70b Chat$?554,411
Poet Vicuna 13b$?964
Flan T5 Xl$0.0046118,875

Similar Models

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Overview

Summary of this model and related resources.

PropertyValue
Creatorreplicate
Model NameLlama 2 70b
Description
Base version of Llama 2, a 70 billion parameter language model from Meta.
TagsText-to-Text
Model LinkView on Replicate
API SpecView on Replicate
Github LinkView on Github
Paper LinkView on Arxiv

Popularity

How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?

PropertyValue
Runs5,481
Model Rank
Creator Rank

Cost

How much does it cost to run this model? How long, on average, does it take to complete a run?

PropertyValue
Cost per Run$-
Prediction Hardware-
Average Completion Time-