🎭 Avatars
Collection
The latest AI-powered technologies usher in a new era of realistic avatars! 🚀
•
75 items
•
Updated
•
88
Damien Tanner
dctanner
AI & ML interests
None yet
Recent Activity
upvoted
a
collection
10 days ago
🎭 Avatars
updated
a dataset
about 1 year ago
sablo/test-ultracm-dolly
updated
a dataset
about 1 year ago
sablo/oasst2_dpo_pairs_en
Organizations
dctanner's activity
upvoted
a
collection
10 days ago
updated
2
datasets
about 1 year ago
liked
a
dataset
about 1 year ago
liked
a
model
about 1 year ago
updated
a
model
about 1 year ago
liked
a
dataset
over 1 year ago
updated
3
models
over 1 year ago
updated
a
dataset
over 1 year ago
replied to
their
post
over 1 year ago
All the HF H4 datasets follow it :)
We could definitely do some like https://huggingface.co/datasets/argilla/distilabel-intel-orca-dpo-pairs, orca etc.
I'm doing hh-rlhf right now so it can be used with alignment-handbook.
liked
a
dataset
over 1 year ago
liked
a
model
over 1 year ago
replied to
their
post
over 1 year ago
It's the same. But I feel we would benefit from a different name than ChatML, which I sometimes see used to refer this format and and the actual chat template format.
posted
an
update
over 1 year ago
Post
As the amount of datasets for fine tuning chat models has grown, there's been a plethora of dataset formats emerge. The most popular of these include the formats used by Alpaca, ShareGPT and Open Assistant datasets. The datasets and their formats have also evolved from single-turn conversation to multi-turn. Many of these formats share similarities (and they all have the same goal), but handling the variations in formats across datasets is often a hassle, and source of potential bugs.
Luckily the community seems to be converging on a simple and elegant chat dataset format: a list with each record being an array with each conversation turn being an object with a role (system, assistant or user) and content. Hugging Face uses this input format in the [Templates for Chat Models](https://huggingface.co/docs/transformers/main/en/chat_templating#how-do-i-use-chat-templates) docs:
Popular datasets like HuggingFaceH4/no_robots follow this format.
To encourage usage of this format, I propose we give it a name: Hugging Face MessagesList format.
The format is defined as:
- Having at least one
- Each messages record is an array containing one or more message turn objects.
- A message turn must have
-
-
This may be a small thing, but having a common dataset format will reduce wasted time data wrangling and help everyone.
Luckily the community seems to be converging on a simple and elegant chat dataset format: a list with each record being an array with each conversation turn being an object with a role (system, assistant or user) and content. Hugging Face uses this input format in the [Templates for Chat Models](https://huggingface.co/docs/transformers/main/en/chat_templating#how-do-i-use-chat-templates) docs:
messages = [
{
"role": "system",
"content": "You are a friendly chatbot who always responds in the style of a pirate",
},
{"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
]Popular datasets like HuggingFaceH4/no_robots follow this format.
To encourage usage of this format, I propose we give it a name: Hugging Face MessagesList format.
The format is defined as:
- Having at least one
messages column of type list.- Each messages record is an array containing one or more message turn objects.
- A message turn must have
role and content keys.-
role should be one of system, assistant or user.-
content is the text content of the message.This may be a small thing, but having a common dataset format will reduce wasted time data wrangling and help everyone.
-
- 5 replies
Future feature: system prompt and chat support
9
21
#459 opened over 1 year ago
by
clefourrier
updated
2
datasets
over 1 year ago
liked
a
dataset
over 1 year ago