# NLP with GPT

### NLP with GPT

[gpt-2](https://github.com/irosyadi/gitbook/blob/master/machine-learning/ai/gpt-2.md)

[gpt-3](https://github.com/irosyadi/gitbook/blob/master/machine-learning/ai/gpt-3.md)

#### GPT Models

* [EleutherAI](https://docs.google.com/document/d/1wfCZBd18DMNt6YcC6boPNMd9qzzH3zpHHfKj4dezk0g/edit#) Huge open source Language Models (i.e like GPT-3)
  * [EleutherAI/gpt-neo: An implementation of model parallel GPT2& GPT3-like models, with the ability to scale up to full GPT3 sizes (and possibly more!), using the mesh-tensorflow library.](https://github.com/EleutherAI/gpt-neo/)
* [Huggingface](https://huggingface.co/) : On a mission to solve NLP, provide many NLP models.
  * [transformer](https://transformer.huggingface.co/) : text generation using transformer GPT2

#### GPT Notes

* [Algpt2 Part 2 - Bilal Khan](https://bkkaggle.github.io/blog/algpt2/2020/07/17/ALGPT2-part-2.html)
* [Twitter for Academic Research](https://developer.twitter.com/en/portal/petition/academic/is-it-right-for-you)

#### GPT

* [OpenAI’s API Now Available with No Waitlist](https://openai.com/blog/api-no-waitlist/)

### GPT Alternatives

* [EleutherAI - text generation testing UI](https://6b.eleuther.ai/)
* [Studio - AI21](https://studio.ai21.com/sign-up)
* [GPT-3 open-source alternatives: GPT-Neo and GPT-J](https://nlpcloud.io/gpt-3-open-source-alternatives-gpt-j-gpt-neo.html)
* [textcortex · PyPI](https://pypi.org/project/textcortex/)

#### NLP

* [Real-time Market Map - 180+ GPT-3 Examples, Demos, Apps, Showcase, and NLP Use-cases - GPT-3 Demo](https://gpt3demo.com/map)
* [kingoflolz/mesh-transformer-jax: Model parallel transformers in JAX and Haiku](https://github.com/kingoflolz/mesh-transformer-jax) Free GPT-J-6B
  * [GPT-J “the open source cousin of GPT-3 everyone can use” - Hacker News](https://news.ycombinator.com/item?id=27727009)
  * [Text Synth](https://bellard.org/textsynth/) demo
  * [EleutherAI - text generation testing UI](https://6b.eleuther.ai/) demo


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://irosyadi.gitbook.io/irosyadi/machine-learning/nlp-gpt.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
