Unleash AI-powered text completion

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November 2, 2022

TextSynth Text Completion

Writing

4,507

5.0(1)1

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Unleash AI-powered text completion

Overview

Overview Releases Pricing Reviews Prompts Pros & Cons Q&A Alternatives Recommendations

Writing1061 0

Text Completion Large Language Models Text Generation Language Model Applications Neural Networks User Customizable ParametersFree + from $20.00

Most popular alternative: Text Generator (67,222 saves)

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TextSynth is an AI tool focused on text completion using large language models. The core function of this tool is to allow users to input a text, which is then completed by the neural network.

This platform provides a variety of completion results, as each attempt returns a uniquely generated completion. TextSynth employs top-performing language models, such as Mistral 7B and Llama2 7B, to generate its outputs.

The tool gives the user control over parameters including top-k, top-p, temperature and maximum tokens, and responses can be halted according to the user's preference.

TextSynth's other features include text translation, converting text to image, and chat. An in-depth understanding of how these various models operate can be gained from the platform's documentation.

It is a versatile platform with a simple interface for language model applications, and a playground module for users to learn and experiment in real time and witness the capabilities of large language models.

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Initial release

December 28, 2021

Initial release of TextSynth Text Completion.

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Pricing

Pricing model

Freemium

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$20/unit

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Pay-as-you-go

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Writing TextSynth Text Completion

Writing

4,507

5.0(1)1

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Speech synthesis2 0

Text to speech94 0

Text & image transcription1 0

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Comments(1)

Le Bazar

Feb 18, 2025

Rated it

One on the best "free" ai for now. There a great free transcription tool, an english text to speech with good quality. The ai can copy your style and if you are good, you can make a humaniser ai with this great tool.

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TextSynth Text Completion was manually vetted by our editorial team and was first featured on November 2nd 2022.

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Pros and Cons

Pros

Multilingual capabilities

Multiple language models

Large parameter models

Fine-tuned models

Adjustable model parameters

Pre-loaded example texts

Wide range of topics

Generates random completions

Versatility in completion tasks

Supports multiple languages

Suitable for coding tasks

User-friendly interface

Flexible stop conditions

Handy for content authors

Effective for translation tasks

Potent for adaptive tasks

Supports several billion parameters

Easily switch between models

Quick text generation

Great for generating ideas

English and French capabilities

Resources for learning and support

Practical for question answering

Good for generating instructions

Wide range of applications

Applicable to linguistics tasks

Valuable for tech tasks

Helpful for text-editing purposes

Useful for creative writing

Efficient for various industries

Functional for text-to-image tasks

Beneficial for programming tasks

Available documentation

Pricing details available

SignUp and Login options

Predetermined text examples

Cool for generating dialogues

Awesome for brainstorming sessions

Efficient text completion

Practical for students

Useful for teachers

Helpful for content creators

Good for technical tasks

Rapid text processing

Applicable to copywriting tasks

Generates diverse text outcomes

View 41 more pros

Cons

Limited language models

Results dependent on randomness

No real-time adjustments

Too much model complexity

User interface is simplistic

Lack of user customizability

No advanced security features

Limits on max tokens

No option for manual completion

No multi-user collaboration option

View 5 more cons

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Q&A

What is TextSynth?

TextSynth is a multilingual, multipurpose AI tool that employs large language models to complete text. Users type in a sentence, and TextSynth by using its neural network, generates a randomly chosen completion.

How does TextSynth utilize large language models to complete text?

TextSynth uses large language models like GPT-J, Boris, GPT-NeoX, and others to predict and generate logical continuations of the user's input text. These models have been trained on extensive corpus of text and can understand context, grammar, and even some nuances of the language.

What are the different models available in TextSynth?

TextSynth offers several models for text generation, such as GPT-J, which is a 6 billion parameter English model, Boris, a fine-tuned version of GPT-J for the French language, GPT-NeoX, which is the largest model with 20 billion parameters, and CodeGen-6B-monotop-k, a model possibly specialized for code generation.

What is GPT-J and how does it work in TextSynth?

GPT-J is a large language model with 6 billion parameters that are used in TextSynth. It's an English model but does have some abilities in other languages, including computer languages. It generates text based on the input, predicting the logical next parts of text.

What is the unique feature of the Boris model in TextSynth?

The unique feature of the Boris model is that it's a fine-tuned version of GPT-J specialized for the French language. This means it is optimized to understand the nuances, idioms, and grammar of French, leading to more accurate and contextually correct text completions.

Can TextSynth generate in languages other than English?

Yes, aside from English, TextSynth can generate text in other languages such as French. It is made possible through the usage of models such as Boris, which is specifically fine-tuned for the French language.

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How can I adjust the parameters of the model in TextSynth?

You can adjust the parameters like 'temperature', 'max tokens', and 'stop at' in TextSynth. The adjustment can be made in the interface while inputting the text, which allows you to control the output in terms of randomness, length, and ending point respectively.

What does 'temperature' refer to in the TextSynth context?

In the TextSynth context, 'temperature' refers to the randomness of the text generation. Higher values of temperature lead to more random outputs, while lower values make the model's output more deterministic and focused.

What are the pre-loaded examples available in TextSynth?

TextSynth comes with several pre-loaded examples such as 'Unicorns that speak English', 'Question-Answer' session, 'C program', 'Cooking Instructions', 'Linux', 'Game of Thrones', 'HTML', 'The Election', and 'Area 51'. Additionally, users can select a 'letter of motivation' or an 'article idea' as an example.

How can I use TextSynth to generate a letter of motivation?

To generate a letter of motivation using TextSynth, you would choose the 'letter of motivation' example from the examples section. After that, based on your input, the AI system would generate the rest of the text.

What is GPT-NeoX and how does it differ from the other models in TextSynth?

GPT-NeoX 20B is the largest model available in TextSynth, with 20 billion parameters. How it differs from other models like GPT-J or Boris is primarily in its size and depth, leading to potentially more accurate, detailed, and nuanced text generation, but these distinctions depend on the context and usage requirements.

Can I generate computer language codes using TextSynth?

Yes, you can generate computer language codes using TextSynth. GPT-J, one of the models used by TextSynth, has abilities in computer languages, making code generation plausible.

Does TextSynth provide any documentation or user guide?

TextSynth does provide documentation that could act as a user guide. The documentation page can be accessed directly from the website.

Is there a sign-up process for using TextSynth?

Yes, there is a sign-up process for using TextSynth. The 'Sign Up' link is available on the website, which navigates users to the sign-up page.

How to log in to the TextSynth platform?

You can log in to the TextSynth platform by clicking on the 'Login' link available on the website. This will navigate you to the login page where you can input your credentials and gain access.

Why are there different types of models in TextSynth, like GPT-J, Boris, and GPT-NeoX?

Having different types of models like GPT-J, Boris, and GPT-NeoX in TextSynth allows the tool to be versatile in generating text completions. Each model has been trained differently and thus excels in different areas. For instance, GPT-J is geared towards English and includes computer languages, Boris is fine-tuned for French language, and GPT-NeoX, the largest model, may offer more nuanced outputs because of its size.

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