_ _ _____ _ ______ _____ ___ _ _ __
| | | ||_ _|| | | _ \|_ _| / _ \ | | | | / /
| | | | | | | | | | | | | | / /_\ \| | | |/ /
| |/\| | | | | | | | | | | | | _ || | | \
\ /\ / _| |_ | |____| |/ / | | | | | || |____| |\ \
\/ \/ \___/ \_____/|___/ \_/ \_| |_/\_____/\_| \_/
The wildtalk module module generates responses for given input using the given model.
In order to change the model used for generation, change this option:
| Option | Description |
|---|---|
| model | one of "convai_gpt", "gpt2", "parlai" |
If no separate wildtalk server is running, this module starts a wildtalk server which can be used by multiple ravestate instances.
This model is based on transfer-learning-conv-ai
It can be used by setting model to "convai_gpt"
| Option | Description |
|---|---|
| temperature | higher value -> more variation in output |
| max_length | maximal length of generated output |
| top_k | <=0: no filtering, >0: keep only top k tokens with highest probability. |
| top_p | <=0.0 no filtering, >0.0: keep smallest subset whose total probability mass >= top_p |
| max_history | maximal number of previous dialog turns to be used for output generation |
This model uses the gpt2 transformer and model from pytorch_transformers. It uses the gpt2-medium dataset.
It can be used by setting model to "gpt2"
| Option | Description |
|---|---|
| temperature | higher value -> more variation in output |
| max_length | maximal length of generated output |
| top_k | <=0: no filtering, >0: keep only top k tokens with highest probability. |
This model uses roboy-parlai.
It can be used by setting model to "parlai"
| Option | Description |
|---|---|
| temperature | higher value -> more variation in output |
| max_length | maximal length of generated output |
| top_k | <=0: no filtering, >0: keep only top k tokens with highest probability. |
A separate server can be used for running the wildtalk generation. This can be configured with the following options:
| Option | Description |
|---|---|
| server_address | Address under which the server is accessible |
| server_port | Port of the server |
To start a standalone server for wildtalk generation, execute this in the /modules folder of ravestate:
python -c "from ravestate_wildtalk import server; server.run(port=<PORTNUMBER>, model=<MODELNAME>)
Note that the model used on server startup will be the model used when accessed from ravestate.