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Create SAVE.md

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## How to save a servable model of Paddle Serving?
- Currently, paddle serving provides a save_model interface for users to access, the interface is similar with `save_inference_model` of Paddle.
``` python
import paddle_serving_client.io as serving_io
serving_io.save_model("imdb_model", "imdb_client_conf",
{"words": data}, {"prediction": prediction},
fluid.default_main_program())
```
`imdb_model` is the server side model with serving configurations. `imdb_client_conf` is the client rpc configurations. Serving has a
dictionary for `Feed` and `Fetch` variables for client to assign. An alias name can be defined for each variable. An example of how to use alias name
is as follows:
``` python
from paddle_serving_client import Client
import sys
client = Client()
client.load_client_config(sys.argv[1])
client.connect(["127.0.0.1:9393"])
for line in sys.stdin:
group = line.strip().split()
words = [int(x) for x in group[1:int(group[0]) + 1]]
label = [int(group[-1])]
feed = {"words": words, "label": label}
fetch = ["acc", "cost", "prediction"]
fetch_map = client.predict(feed=feed, fetch=fetch)
print("{} {}".format(fetch_map["prediction"][1], label[0]))
```
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