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Suppress spurious markdown lint errors in README (#254)
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* Suppress line-length violation in README

* Suppress line-length violation in README

* Ignore no-inline-html lint error

* Add the mock parameter selector back in

* Fix lint errors in parameter selector

* Change markdownlint config to allow 120-length lines

* Update .markdownlint.yaml

* Update README.md

---------

Co-authored-by: zhaochen20 <zhaochenyang20@gmail.com>
Co-authored-by: Graham Neubig <neubig@gmail.com>
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4 changes: 4 additions & 0 deletions .markdownlint.yaml
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MD013:
line_length: 120
code_blocks: false
MD033: false
20 changes: 10 additions & 10 deletions README.md
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Expand Up @@ -10,6 +10,7 @@ special-purpose model that is conducive for deployment.
<img width="360" alt="prompt2model_teaser" src="https://github.com/neulab/prompt2model/assets/2577384/39ca466a-5355-4d82-8312-303e52ba2bca">

## Quick Start

```bash
pip install .
```
Expand All @@ -30,22 +31,22 @@ export OPENAI_API_KEY=<your key>
```

You can then run
```

```bash
python cli_demo.py
```
to
create a small model from a prompt, as shown in

to
create a small model from a prompt, as shown in
the demo video below. This script must be run on a
device with an internet connection to access the OpenAI
API. For best results, run
this script on a device with a GPU for training
your model.

## Demo
https://github.com/neulab/prompt2model/assets/2577384/8d73394b-3028-4a0b-bdc3-c127082868f2



<https://github.com/neulab/prompt2model/assets/2577384/8d73394b-3028-4a0b-bdc3-c127082868f2>

## How to Write a Good Prompt

Expand Down Expand Up @@ -82,7 +83,6 @@ Also, we recommend providing several precise examples
in the specified format and inquiring with ChatGPT
about the format and scope of your examples.


## Components

The `prompt2model` package is composed
Expand All @@ -107,15 +107,15 @@ refer to [CONTRIBUTING.md](CONTRIBUTING.md),
or reach out to [@vijaytarian](https://twitter.com/vijaytarian)
and [@ChenytangZhao](https://twitter.com/ChenytangZhao).


## Cite

We have [written a paper describing Prompt2Model in detail](https://arxiv.org/abs/YYMM.XXXXX).

If you use Prompt2Model in your research, please cite our paper:
```

```bibtex
@misc{prompt2model,
title={Prompt2Model: Generating Deployable Models from Natural Language Instructions},
title={Prompt2Model: Generating Deployable Models from Natural Language Instructions},
author={Vijay Viswanathan and Chenyang Zhao and Amanda Bertsch and Tongshuang Wu and Graham Neubig},
year={2023},
eprint={YYMM.XXXXX},
Expand Down

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