OpenChat: Easy to use opensource chatting framework via neural networks
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OpenChat is easy to use opensource chatting framework.
OpenChat supports 40+ dialogue model based on neural networks.
You can talk with AI with only one line of code.
OpenChat supports 40+ dialogue models based on neural networks.
Use these names as parameter model='name'
when you create OpenChat
.
Click here if you want to check supported models.
gptneo.small
gptneo.medium
gptneo.large
gptneo.xlarge
blender.small
blender.medium
blender.large
blender.xlarge
blender.xxlarge
dialogpt.small
dialogpt.medium
dialogpt.large
dodecathlon.all_tasks_mt
dodecathlon.convai2
dodecathlon.wizard_of_wikipedia
dodecathlon.empathetic_dialogues
dodecathlon.eli5
dodecathlon.reddit
dodecathlon.twitter
dodecathlon.ubuntu
dodecathlon.image_chat
dodecathlon.cornell_movie
dodecathlon.light_dialog
dodecathlon.daily_dialog
reddit.xlarge
reddit.xxlarge
safety.offensive
safety.sensitive
unlikelihood.wizard_of_wikipedia.context_and_label
unlikelihood.wizard_of_wikipedia.context
unlikelihood.wizard_of_wikipedia.label
unlikelihood.convai2.context_and_label
unlikelihood.convai2.context
unlikelihood.convai2.label
unlikelihood.convai2.vocab.alpha.1e-0
unlikelihood.convai2.vocab.alpha.1e-1
unlikelihood.convai2.vocab.alpha.1e-2
unlikelihood.convai2.vocab.alpha.1e-3
unlikelihood.eli5.context_and_label
unlikelihood.eli5.context
unlikelihood.eli5.label
wizard_of_wikipedia.end2end_generator
Just import and create a object. That's all.
>> > from openchat import OpenChat
>> > OpenChat (model = "blender.medium" , device = "cpu" )
Set param device='cuda'
If you want to use GPU acceleration.
>> > from openchat import OpenChat
>> > OpenChat (model = "blender.medium" , device = "cuda" )
Set param device='cuda:n'
If you want to use a specific GPU.
>> > from openchat import OpenChat
>> > OpenChat (model = "blender.medium" , device = "cuda:2" ) # <--- use 3rd GPU
>> > OpenChat (model = "blender.medium" , device = "cuda:0" ) # <--- use 1st GPU
Set **kwargs
if you want to change decoding options.
method (str): one of ["greedy", "beam", "top_k", "nucleus"]
,
num_beams (int): size of beam search
top_k (int): K value for top-k sampling
top_p: (float): P value for nucleus sampling
no_repeat_ngram_size (int): beam search n-gram blocking size for removing repetition,
length_penalty (float): length penalty (1.0=None, UP=Longer, DOWN=Shorter)
Decoding options must be keyword argument
not positional argument
.
>> > from openchat import OpenChat
>> > OpenChat (
... model = "blender.medium" ,
... device = "cpu" ,
... method = "top_k" ,
... top_k = 20 ,
... no_repeat_ngram_size = 3 ,
... length_penalty = 0.6 ,
... )
For safety.offensive
model, parameter method
must be one of ["both", "string-match", "bert"]
>> > from openchat import OpenChat
>> > OpenChat (
... model = "safety.offensive" ,
... device = "cpu"
... method = "both" # ---> both, string-match, bert
... )
The GPT-Neo model was released in the EleutherAI/gpt-neo repository.
It is a GPT2 like causal language model trained on the Pile dataset.
Openchat supports the above Prompt based dialogues via GPT-Neo.
Below models provides custom prompt setting. (*
means all models)
ConvAI2 is one of the most famous conversational AI challenges about a persona.
Openchat provides custom persona setting like above image.
Below models provides custom perona setting. (*
means all models)
blender.*
dodecathlon.convai2
unlikelihood.convai2.*
Wizard of wikipedia is one of most famous knowledge grounded dialogue dataset.
Openchat provides custom topic setting like above image.
Below models provides custom topic setting. (*
means all models)
wizard_of_wikipedia.end2end_generator
dodecathlon.wizard_of_wikipedia
unlikelihood.wizard_of_wikipedia.*
Openchat provides a dialog safety model to help you design conversation model.
Below models provides dialog safety features.
safety.offensive
: offensive words classification
safety.sensitive
: sensitive topic classification
Openchat is not a finished, but a growing library.
I plan to add the following features in the near future.
Copyright 2021 Hyunwoong Ko.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.