Install stalled with Linux/Docker

[mgifford]

I think I'm following the steps right, but it seems like it is stalled here:

$ docker container run --name crest_container -p 3000:3000 crest 
[nltk_data] Downloading package stopwords to /root/nltk_data...
[nltk_data]   Unzipping corpora/stopwords.zip.
[nltk_data] Downloading package punkt to /root/nltk_data...
[nltk_data]   Unzipping tokenizers/punkt.zip.
[nltk_data] Downloading package stopwords to /root/nltk_data...
[nltk_data]   Package stopwords is already up-to-date!
[nltk_data] Downloading package punkt to /root/nltk_data...
[nltk_data]   Package punkt is already up-to-date!
Downloading: 100%|██████████| 899k/899k [00:00<00:00, 4.57MB/s]
Downloading: 100%|██████████| 456k/456k [00:00<00:00, 3.57MB/s]
Downloading: 100%|██████████| 239/239 [00:00<00:00, 111kB/s]
Downloading: 100%|██████████| 270/270 [00:00<00:00, 165kB/s]
Downloading: 100%|██████████| 563/563 [00:00<00:00, 318kB/s]
Downloading: 100%|██████████| 501M/501M [01:22<00:00, 6.04MB/s] 
Some weights of the model checkpoint at gargam/roberta-base-crest were not used when initializing RobertaForSequenceClassification: ['roberta.pooler.dense.weight', 'roberta.pooler.dense.bias']
- This IS expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
 * Serving Flask app 'server' (lazy loading)
 * Environment: production
   WARNING: This is a development server. Do not use it in a production deployment.
   Use a production WSGI server instead.
 * Debug mode: on
[nltk_data] Downloading package stopwords to /root/nltk_data...
[nltk_data]   Package stopwords is already up-to-date!
[nltk_data] Downloading package punkt to /root/nltk_data...
[nltk_data]   Package punkt is already up-to-date!
[nltk_data] Downloading package stopwords to /root/nltk_data...
[nltk_data]   Package stopwords is already up-to-date!
[nltk_data] Downloading package punkt to /root/nltk_data...
[nltk_data]   Package punkt is already up-to-date!
Some weights of the model checkpoint at gargam/roberta-base-crest were not used when initializing RobertaForSequenceClassification: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']
- This IS expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).

Before that I did successfully run the other command

$ docker build -t crest .
Sending build context to Docker daemon  24.36MB
Step 1/10 : FROM python:3.8
 ---> e7d3be492e61
Step 2/10 : COPY ./requirements.txt .
 ---> Using cache
 ---> 3109834875a2
Step 3/10 : RUN pip install -r requirements.txt
 ---> Using cache
 ---> 53c512132200
Step 4/10 : RUN curl https://chromedriver.storage.googleapis.com/2.31/chromedriver_linux64.zip -o /usr/local/bin/chromedriver
 ---> Using cache
 ---> 70cd8dc112a3
Step 5/10 : RUN chmod +x /usr/local/bin/chromedriver
 ---> Using cache
 ---> 717468bc952e
Step 6/10 : COPY src/ /usr/src/app/
 ---> Using cache
 ---> 34c9954c31cf
Step 7/10 : WORKDIR /usr/src/app/
 ---> Using cache
 ---> 61708bf76838
Step 8/10 : ENV PYTHONPATH "${PYTHONPATH}:/usr/src/app/"
 ---> Using cache
 ---> 45a421178eae
Step 9/10 : EXPOSE 3000
 ---> Using cache
 ---> 98f19373ae03
Step 10/10 : CMD ["python", "/usr/src/app/crest/server.py"]
 ---> Using cache
 ---> b90d92c26f89
Successfully built b90d92c26f89
Successfully tagged crest:latest

I'm not sure what I'm missing.

Docker version 20.10.6, build 370c289 #82-Ubuntu SMP Wed Apr 14 17:39:42 UTC 2021

Dockerfile FROM ubuntu