Skip to content

Commit

Permalink
Browse files Browse the repository at this point in the history
  • Loading branch information
xtonev committed Nov 8, 2019
2 parents 53c1d7c + 7af52f3 commit e0b4e52
Showing 1 changed file with 4 additions and 3 deletions.
7 changes: 4 additions & 3 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -17,12 +17,12 @@ Consider using TopicNet if:
```TopicNet``` provides an infrastructure for your prototyping (```Experiment``` class) and helps to observe results of your actions via ```viewers``` module.

### How to start?
Define `TopicModel` from an ARTM model at hand or with help from `model_constructor` module. Then create an `Experiment`, assigning a root position to this model. Further, you can define a set of training stages by the functionality provided by the `cooking_machine.cubes` module.
Define `TopicModel` from an ARTM model at hand or with help from `model_constructor` module, where you can set models main parameters. Then create an `Experiment`, assigning a root position to this model and path to store your experiment. Further, you can define a set of training stages by the functionality provided by the `cooking_machine.cubes` module.

---
## How to install TopicNet
**Core library functionality is based on BigARTM library** which requires manual installation.
To avoid that you can use [docker images](https://hub.docker.com/r/xtonev/bigartm/tags) with preinstalled BigARTM library in them.
To avoid that you can use [docker images](https://hub.docker.com/r/xtonev/bigartm/tags) with preinstalled different versions of BigARTM library in them.

#### Using docker image
```
Expand Down Expand Up @@ -90,12 +90,13 @@ custom_score_dict = {'SpecificSparsity': CustomScore()}
tm = TopicModel(model_artm, model_id='Groot', custom_scores=custom_score_dict)
```
#### Define experiment
For further model training and tuning `Experiment` is necessary:
```
from topicnet.cooking_machine.experiment import Experiment
experiment = Experiment(experiment_id="simple_experiment", save_path="experiments", topic_model=tm)
```
#### Toy with the cubes
Defining a next stage of the model training:
Defining a next stage of the model training to select a decorrelator parameter:
```
from topicnet.cooking_machine.cubes import RegularizersModifierCube
Expand Down

0 comments on commit e0b4e52

Please sign in to comment.