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Commit f35fa1d9 authored by Jeff Wu's avatar Jeff Wu
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push 774M model

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......@@ -27,8 +27,9 @@ pip3 install -r requirements.txt
Download the model data
```
python3 download_model.py 117M
python3 download_model.py 345M
python3 download_model.py 124M
python3 download_model.py 355M
python3 download_model.py 774M
```
## Docker Installation
......
......@@ -5,5 +5,6 @@ RUN mkdir /gpt-2
WORKDIR /gpt-2
ADD . /gpt-2
RUN pip3 install -r requirements.txt
RUN python3 download_model.py 117M
RUN python3 download_model.py 345M
RUN python3 download_model.py 124M
RUN python3 download_model.py 355M
RUN python3 download_model.py 774M
......@@ -14,5 +14,6 @@ RUN mkdir /gpt-2
WORKDIR /gpt-2
ADD . /gpt-2
RUN pip3 install -r requirements.txt
RUN python3 download_model.py 117M
RUN python3 download_model.py 345M
RUN python3 download_model.py 124M
RUN python3 download_model.py 355M
RUN python3 download_model.py 774M
......@@ -4,9 +4,11 @@
Code from the paper ["Language Models are Unsupervised Multitask Learners"](https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf).
We have currently released small (117M parameter) and medium (345M parameter) versions of GPT-2. While we have not released the larger models, we have [released a dataset](https://github.com/openai/gpt-2-output-dataset) for researchers to study their behaviors.
We have currently released small (124M parameter), medium (355M parameter), and large (774M parameter) versions of GPT-2<sup>*</sup>, with only the full model as of yet unreleased. We have also [released a dataset](https://github.com/openai/gpt-2-output-dataset) for researchers to study their behaviors.
See more details in our [blog post](https://blog.openai.com/better-language-models/).
You can read about GPT-2 and release decisions in our [original blog post](https://blog.openai.com/better-language-models/) and [6 month follow-up post](https://openai.com/blog/gpt-2-6-month-follow-up/).
<sup>*</sup> *Note that our original parameter counts were wrong due to an error (in our previous blog posts and paper). Thus you may have seen small referred to as 117M and medium referred to as 345M.*
## Usage
......
......@@ -4,7 +4,7 @@ import requests
from tqdm import tqdm
if len(sys.argv) != 2:
print('You must enter the model name as a parameter, e.g.: download_model.py 117M')
print('You must enter the model name as a parameter, e.g.: download_model.py 124M')
sys.exit(1)
model = sys.argv[1]
......
......@@ -9,7 +9,7 @@ import tensorflow as tf
import model, sample, encoder
def sample_model(
model_name='117M',
model_name='124M',
seed=None,
nsamples=0,
batch_size=1,
......@@ -20,7 +20,7 @@ def sample_model(
):
"""
Run the sample_model
:model_name=117M : String, which model to use
:model_name=124M : String, which model to use
:seed=None : Integer seed for random number generators, fix seed to
reproduce results
:nsamples=0 : Number of samples to return, if 0, continues to
......
......@@ -9,7 +9,7 @@ import tensorflow as tf
import model, sample, encoder
def interact_model(
model_name='117M',
model_name='124M',
seed=None,
nsamples=1,
batch_size=1,
......@@ -20,7 +20,7 @@ def interact_model(
):
"""
Interactively run the model
:model_name=117M : String, which model to use
:model_name=124M : String, which model to use
:seed=None : Integer seed for random number generators, fix seed to reproduce
results
:nsamples=1 : Number of samples to return total
......
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