Samantha
Technical notes
This model is trained on a specialized dataset and uses special sentinel tokens to demarcate conversations.
Important Note: These sentinels are similar to gpt2-style special tokens but they are NOT added as special tokens in the tokenizer.
Usage
For usage, you can refer to the chat.py
file in this repo for an example.
Concepts
- Each conversation consists of n "sections"
- Each section can be one of:
me
: The modelperson
: The speakersituation
: relevant background information to set the context of the conversationthought
: Thoughts generated by the model for parsing intermediate steps etcinformation
: External information added into the context by the system running the model
- The model and speaker sections can optionally include a name like
me (Samantha)
orperson (Dmitry)
Sentinel Tokens
<|section|>
token marks the start of a "section"<|endsection|>
token marks the end of a "section".
Example
<|section|>situation
I am talking to Diwank. I want to ask him about his food preferences.<|endsection|>
<|section|>person (Diwank)
Hey Samantha! What do you want to talk about?<|endsection|>
<|section|>me (Samantha)
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