[distribution] prepare a list of actions to publish and promote the API
more on this here: https://docs.google.com/document/d/1XgJ8BuPZ2mM_VJ7K3DtwlU_AQSeSgSi8HD40XjE3b34/edit

Work with @huggingface/datasets and @osanseviero + avocado team to push the publication of the API

Tasks:
- [ ] better discovery from the Hub showing how to use the API: https://github.com/huggingface/moon-landing/issues/3722
- [ ] incorporate content into the hub docs https://huggingface.co/docs/hub/index
- [ ] incorporate content into the datasets docs https://huggingface.co/docs/datasets/index. Might be in several places: in the intro, as a separate section (port/API), and as a side note in every relevant API reference function (ie. get_split_names -> the information can also be obtained from a REST API...) 


Other ideas
- [ ] prepare a list of announcements:
  - public API
  - why we build it or why we think it's useful: access metadata and data from the Hub datasets through a web API (ie without Python), help the community build exploration tools easily, increasing the offer of tools to connect to the Hub. Currently: allows getting the splits, the first rows, the columns, and their types (features)
  - feedback: what would you want to access through the API? Through GitHub: huggingface/datasets, label "API"? Other channels?
  - roadmap: the future features. Possibly:
    - random access to the rows,
    - statistics on the columns,
    - other preprocessed information (analysis, metrics) about the datasets, eg: detection of biases, distribution of the classes, size of the images, presence or not of faces in image datasets, distribution of images in a class, number of speakers in audio datasets, presence of noise, ie real-world not-clean audio files, in audio datasets.
    - recommendation system, to get a list of other datasets with the same format (same columns with the same type).
    - compute embeddings of the datasets
- [x] announcement materials: code highlighted in [carbon](https://carbon.now.sh/?bg=rgba%28171%2C+184%2C+195%2C+1%29&t=panda-syntax&wt=none&l=python&width=751&ds=true&dsyoff=20px&dsblur=68px&wc=true&wa=false&pv=56px&ph=56px&ln=false&fl=1&fm=Hack&fs=14px&lh=133%25&si=false&es=2x&wm=false), show the postman collection, prepare appealing visuals (eg https://twitter.com/mervenoyann/status/1557753337554034688 or https://twitter.com/mervenoyann/status/1562838963072643072)
- [ ] channels
  - [ ] twitter
  - [ ] linkedin
  - [ ] discord: <strike>one specific message per channel (computer vision, audio, etc)</strike> (<- too much spam). Better use "announcements"
  - [x] <strike>discuss forum</strike> -> not for announcements. Might help for feedback
  - [ ] youtube?
  - [x] <strike>blog</strike>
  - [ ] direct messages to Paperwithcode, Arxiv, Kaggle
- [ ] showcase:
  - [x] observable notebook
  - [ ] HF space (see https://huggingface.co/spaces/julien-c/push-model-from-web for example for a pure browser example)
  - [x] an app that shows all the datasets (bird-eye view), "like" https://lexica.art/ or https://projector.tensorflow.org/?
  - [ ] HF spaces: a dataset selector
  - [ ] pure JS ML using the datasets server to get the data, eg https://mlconsole.com/ / tf.js (even if we only have the first 100 rows for now)
  - [ ] open source a standalone viewer in e.g. Svelte or React or vanilla

Publish the API on specialized sites:
- [x] create a [Postman collection](https://www.postman.com/collection/) ([idea](https://huggingface.slack.com/archives/C0311GZ7R6K/p1662587094571639?thread_ts=1662564194.339629&cid=C0311GZ7R6K)). Done, here it is: https://www.postman.com/huggingface/workspace/hugging-face-apis/documentation/23242779-d068584e-96d1-4d92-a703-7cb12cbd8053, in the https://www.postman.com/huggingface team.
  - [ ] try to get a RT from https://twitter.com/getpostman (32K followers)
- [x] create a public API on [RapidAPI](https://rapidapi.com/). Done here: https://rapidapi.com/hugging-face-hugging-face-default/api/hugging-face-datasets-api/, in the https://rapidapi.com/organization/hugging-face org.
  - [ ] try to get a RT from https://twitter.com/rapid_api (89K followers)

ideas by @julien-c @lhoestq @albertvillanova @thomwolf @NimaBoscarino @merveenoyan 
[distribution] prepare a list of actions to publish and promote the API: more on this here: https://docs.google.com/document/d/1XgJ8BuPZ2mM_VJ7K3DtwlU_AQSeSgSi8HD40XjE3b34/edit

Work with @huggingface/datasets and @osanseviero + avocado team to push the publication of the API

Tasks:
- [ ] better discovery from the Hub showing how to use the API: https://github.com/huggingface/moon-landing/issues/3722
- [ ] incorporate content into the hub docs https://huggingface.co/docs/hub/index
- [ ] incorporate content into the datasets docs https://huggingface.co/docs/datasets/index. Might be in several places: in the intro, as a separate section (port/API), and as a side note in every relevant API reference function (ie. get_split_names -> the information can also be obtained from a REST API...) 


Other ideas
- [ ] prepare a list of announcements:
  - public API
  - why we build it or why we think it's useful: access metadata and data from the Hub datasets through a web API (ie without Python), help the community build exploration tools easily, increasing the offer of tools to connect to the Hub. Currently: allows getting the splits, the first rows, the columns, and their types (features)
  - feedback: what would you want to access through the API? Through GitHub: huggingface/datasets, label "API"? Other channels?
  - roadmap: the future features. Possibly:
    - random access to the rows,
    - statistics on the columns,
    - other preprocessed information (analysis, metrics) about the datasets, eg: detection of biases, distribution of the classes, size of the images, presence or not of faces in image datasets, distribution of images in a class, number of speakers in audio datasets, presence of noise, ie real-world not-clean audio files, in audio datasets.
    - recommendation system, to get a list of other datasets with the same format (same columns with the same type).
    - compute embeddings of the datasets
- [x] announcement materials: code highlighted in [carbon](https://carbon.now.sh/?bg=rgba%28171%2C+184%2C+195%2C+1%29&t=panda-syntax&wt=none&l=python&width=751&ds=true&dsyoff=20px&dsblur=68px&wc=true&wa=false&pv=56px&ph=56px&ln=false&fl=1&fm=Hack&fs=14px&lh=133%25&si=false&es=2x&wm=false), show the postman collection, prepare appealing visuals (eg https://twitter.com/mervenoyann/status/1557753337554034688 or https://twitter.com/mervenoyann/status/1562838963072643072)
- [ ] channels
  - [ ] twitter
  - [ ] linkedin
  - [ ] discord: <strike>one specific message per channel (computer vision, audio, etc)</strike> (<- too much spam). Better use "announcements"
  - [x] <strike>discuss forum</strike> -> not for announcements. Might help for feedback
  - [ ] youtube?
  - [x] <strike>blog</strike>
  - [ ] direct messages to Paperwithcode, Arxiv, Kaggle
- [ ] showcase:
  - [x] observable notebook
  - [ ] HF space (see https://huggingface.co/spaces/julien-c/push-model-from-web for example for a pure browser example)
  - [x] an app that shows all the datasets (bird-eye view), "like" https://lexica.art/ or https://projector.tensorflow.org/?
  - [ ] HF spaces: a dataset selector
  - [ ] pure JS ML using the datasets server to get the data, eg https://mlconsole.com/ / tf.js (even if we only have the first 100 rows for now)
  - [ ] open source a standalone viewer in e.g. Svelte or React or vanilla

Publish the API on specialized sites:
- [x] create a [Postman collection](https://www.postman.com/collection/) ([idea](https://huggingface.slack.com/archives/C0311GZ7R6K/p1662587094571639?thread_ts=1662564194.339629&cid=C0311GZ7R6K)). Done, here it is: https://www.postman.com/huggingface/workspace/hugging-face-apis/documentation/23242779-d068584e-96d1-4d92-a703-7cb12cbd8053, in the https://www.postman.com/huggingface team.
  - [ ] try to get a RT from https://twitter.com/getpostman (32K followers)
- [x] create a public API on [RapidAPI](https://rapidapi.com/). Done here: https://rapidapi.com/hugging-face-hugging-face-default/api/hugging-face-datasets-api/, in the https://rapidapi.com/organization/hugging-face org.
  - [ ] try to get a RT from https://twitter.com/rapid_api (89K followers)

ideas by @julien-c @lhoestq @albertvillanova @thomwolf @NimaBoscarino @merveenoyan 