GPT-2 has a wide range of potential use cases for technical audiences. It can be used for text generation tasks such as language modeling, story writing, or content creation for websites or blogs. The model can also be fine-tuned for specific downstream tasks like sentiment analysis, question answering, or chatbot development. The ability to extract features useful for downstream tasks from the model's inner representation of the English language makes it a valuable tool for natural language processing tasks. Additionally, GPT-2 can be used for text summarization, text completion, and text correction tasks. With its impressive performance without fine-tuning, GPT-2 offers a powerful tool for generating high-quality, contextually relevant text. Possible products or practical uses of this model include AI-powered content generation tools, language modeling APIs, chatbot frameworks, and automated writing assistants.
- Cost per run
- Avg run time
|Bert Large Uncased Whole Word Masking Finetuned Squad||$?||294,128|
|Bert Large Cased Whole Word Masking||$?||4,430|
|Xlm Roberta Large Finetuned Conll02 Dutch||$?||378|
|Xlm Roberta Large Finetuned Conll02 Spanish||$?||171|
You can use this area to play around with demo applications that incorporate the Gpt2 model. These demos are maintained and hosted externally by third-party creators. If you see an error, message me on Twitter.
Summary of this model and related resources.
Test the whole generation capabilities here: https://transformer.huggingface.co/doc/gpt2-large...Read more »
|Model Link||View on HuggingFace|
|API Spec||View on HuggingFace|
|Github Link||No Github link provided|
|Paper Link||No paper link provided|
How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?
How much does it cost to run this model? How long, on average, does it take to complete a run?
|Cost per Run||$-|
|Average Completion Time||-|