Fix parameter server command line options in README (#776)

Author: osalpekar

distributed/rpc/parameter_server/README.md

@@ -3,7 +3,7 @@
 This is a basic example of RPC-based training that uses several trainers remotely train a model hosted on a server. 
 
 To run the example locally, run the following command worker for the server and each worker you wish to spawn, in separate terminal windows:
-`python rpc_parameter_server.py --world_size=WORLD_SIZE --rank=RANK`. For example, for a master node with world size of 2, the command would be `python rpc_parameter_server.py ---world_size=2 --rank=0`. The trainer can then be launched with the command `python rpc_parameter_server.py --world_size=2 --rank=1` in a separate window, and this will begin training with one server and a single trainer.
+`python rpc_parameter_server.py --world_size=WORLD_SIZE --rank=RANK`. For example, for a master node with world size of 2, the command would be `python rpc_parameter_server.py --world_size=2 --rank=0`. The trainer can then be launched with the command `python rpc_parameter_server.py --world_size=2 --rank=1` in a separate window, and this will begin training with one server and a single trainer.
 
 Note that for demonstration purposes, this example supports only between 0-2 GPUs, although the pattern can be extended to make use of additional GPUs. To configure the number of GPUs, pass in `--num_gpus=N` to your training command.