Skip to content

Readme: Filename conforming to datasets/ + install tensorflow #75

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Readme: Filename conforming to datasets/ + install tensorflow #75

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 3 additions & 3 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@ textgen.generate()
The included model can easily be trained on new texts, and can generate appropriate text *even after a single pass of the input data*.

```python
textgen.train_from_file('hacker-news-2000.txt', num_epochs=1)
textgen.train_from_file('hacker_news_2000.txt', num_epochs=1)
textgen.generate()
```

Expand Down Expand Up @@ -79,7 +79,7 @@ This can add a *human touch* to the output; it feels like you're the writer! ([r
textgenrnn can be installed [from pypi](https://pypi.python.org/pypi/textgenrnn) via `pip`:

```sh
pip3 install textgenrnn
pip3 install textgenrnn tensorflow
```

You can view a demo of common features and model configuration options in [this Jupyter Notebook](/docs/textgenrnn-demo.ipynb).
Expand Down Expand Up @@ -156,4 +156,4 @@ Andrej Karpathy for the original proposal of the char-rnn via the blog post [The

MIT

Attention-layer code used from [DeepMoji](https://github.com/bfelbo/DeepMoji) (MIT Licensed)
Attention-layer code used from [DeepMoji](https://github.com/bfelbo/DeepMoji) (MIT Licensed)