add contributors md and move dev docs out

CONTRIBUTORS.md

@@ -0,0 +1,17 @@
+# Contributors (alphabetically)
+
+* **[madisonmay](https://github.com/madisonmay)**
+
+  Added Dockerfiles
+
+* **[Margaret Mitchell et al](https://arxiv.org/abs/1810.03993)**
+
+  Our [usage](./readme#usage) writeup was loosely inspired by the paper
+  [Model Cards for Model Reporting](https://arxiv.org/abs/1810.03993)
+  and related conversations with some of the authors.
+
+* **[webproduktion01](https://github.com/webproduktion01)**
+
+  Ported download script to python.
+
+**[Full code contributors list](https://github.com/openai/gpt-2/contributors).**

DEVELOPERS.md

@@ -0,0 +1,85 @@
+# Installation
+
+Git clone this repository, and `cd` into directory for remaining commands
+```
+git clone https://github.com/openai/gpt-2.git && cd gpt-2
+```
+
+Then, follow instructions for either native or Docker installation.
+
+## Native Installation
+
+All steps can optionally be done in a virtual environment using tools such as `virtualenv` or `conda`.
+
+Install tensorflow 1.12 (with GPU support, if you have a GPU and want everything to run faster)
+```
+pip3 install tensorflow==1.12.0
+```
+or
+```
+pip3 install tensorflow-gpu==1.12.0
+```
+
+Install other python packages:
+```
+pip3 install -r requirements.txt
+```
+
+Download the model data
+```
+python3 download_model.py 117M
+```
+
+## Docker Installation
+
+Build the Dockerfile and tag the created image as `gpt-2`:
+```
+docker build --tag gpt-2 -f Dockerfile.gpu . # or Dockerfile.cpu
+```
+
+Start an interactive bash session from the `gpt-2` docker image.
+
+You can opt to use the `--runtime=nvidia` flag if you have access to a NVIDIA GPU
+and a valid install of [nvidia-docker 2.0](https://github.com/nvidia/nvidia-docker/wiki/Installation-(version-2.0)).
+```
+docker run --runtime=nvidia -it gpt-2 bash
+```
+
+# Running
+
+| WARNING: Samples are unfiltered and may contain offensive content. |
+| --- |
+
+Some of the examples below may include Unicode text characters. Set the environment variable:
+```
+export PYTHONIOENCODING=UTF-8
+```
+to override the standard stream settings in UTF-8 mode.
+
+## Unconditional sample generation
+
+To generate unconditional samples from the small model:
+```
+python3 src/generate_unconditional_samples.py | tee /tmp/samples
+```
+There are various flags for controlling the samples:
+```
+python3 src/generate_unconditional_samples.py --top_k 40 --temperature 0.7 | tee /tmp/samples
+```
+
+To check flag descriptions, use:
+```
+python3 src/generate_unconditional_samples.py -- --help
+```
+
+## Conditional sample generation
+
+To give the model custom prompts, you can use:
+```
+python3 src/interactive_conditional_samples.py --top_k 40
+```
+
+To check flag descriptions, use:
+```
+python3 src/interactive_conditional_samples.py -- --help
+```

README.md

@@ -22,91 +22,13 @@ Please [let us know](mailto:languagequestions@openai.com) if you’re doing inte
 - Potential malicious use cases and defenses against them (e.g. the detectability of synthetic text)
 - The extent of problematic content (e.g. bias) being baked into the models and effective mitigations
 
-## Installation
+## Development
 
-Git clone this repository, and `cd` into directory for remaining commands
+See [DEVELOPERS.md](./DEVELOPERS.md)
-```
-git clone https://github.com/openai/gpt-2.git && cd gpt-2
-```
 
-Then, follow instructions for either native or Docker installation.
+## Contributors
 
-### Native Installation
+See [CONTRIBUTORS.md](./CONTRIBUTORS.md)
-
-All steps can optionally be done in a virtual environment using tools such as `virtualenv` or `conda`.
-
-Install tensorflow 1.12 (with GPU support, if you have a GPU and want everything to run faster)
-```
-pip3 install tensorflow==1.12.0
-```
-or
-```
-pip3 install tensorflow-gpu==1.12.0
-```
-
-Install other python packages:
-```
-pip3 install -r requirements.txt
-```
-
-Download the model data
-```
-python3 download_model.py 117M
-```
-
-### Docker Installation
-
-Build the Dockerfile and tag the created image as `gpt-2`:
-```
-docker build --tag gpt-2 -f Dockerfile.gpu . # or Dockerfile.cpu
-```
-
-Start an interactive bash session from the `gpt-2` docker image.
-
-You can opt to use the `--runtime=nvidia` flag if you have access to a NVIDIA GPU
-and a valid install of [nvidia-docker 2.0](https://github.com/nvidia/nvidia-docker/wiki/Installation-(version-2.0)).
-```
-docker run --runtime=nvidia -it gpt-2 bash
-```
-
-## Sampling scripts
-
-| WARNING: Samples are unfiltered and may contain offensive content. |
-| --- |
-
-Some of the examples below may include Unicode text characters. Set the environment variable:
-```
-export PYTHONIOENCODING=UTF-8
-```
-to override the standard stream settings in UTF-8 mode.
-
-### Unconditional sample generation
-
-To generate unconditional samples from the small model:
-```
-python3 src/generate_unconditional_samples.py | tee /tmp/samples
-```
-There are various flags for controlling the samples:
-```
-python3 src/generate_unconditional_samples.py --top_k 40 --temperature 0.7 | tee /tmp/samples
-```
-
-To check flag descriptions, use:
-```
-python3 src/generate_unconditional_samples.py -- --help
-```
-
-### Conditional sample generation
-
-To give the model custom prompts, you can use:
-```
-python3 src/interactive_conditional_samples.py --top_k 40
-```
-
-To check flag descriptions, use:
-```
-python3 src/interactive_conditional_samples.py -- --help
-```
 
 ## GPT-2 samples