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@@ -23,13 +23,13 @@ If you want to run examples, make sure you have [git-lfs](https://git-lfs.github
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To quickly tryout RedisAI, launch an instance using docker:
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```sh
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docker run -p 6379:6379 -it --rm redislabs/redisai
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docker run -p 6379:6379 -it --rm redislabs/redisai:edge-cpu
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```
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For docker instance with GPU support, you can launch it from `tensorwerk/redisai-gpu`
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```sh
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docker run -p 6379:6379 --gpus all -it --rm redislabs/redisai:latest-gpu
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docker run -p 6379:6379 --gpus all -it --rm redislabs/redisai:edge-gpu
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```
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But if you'd like to build the docker image, you need a machine that has Nvidia driver (CUDA 10.0), nvidia-container-toolkit and Docker 19.03+ installed. For detailed information, checkout [nvidia-docker documentation](https://github.com/NVIDIA/nvidia-docker)
@@ -46,7 +46,7 @@ Note that Redis config is located at `/usr/local/etc/redis/redis.conf` which can
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On the client, set the model
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```sh
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redis-cli -x AI.MODELSET foo TF CPU INPUTS a b OUTPUTS c BLOB < tests/test_data/graph.pb
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redis-cli -x AI.MODELSTORE foo TF CPU INPUTS 2 a b OUTPUTS 1 c BLOB < tests/test_data/graph.pb
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```
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Then create the input tensors, run the computation graph and get the output tensor (see `load_model.sh`). Note the signatures:
@@ -122,6 +122,9 @@ Some languages have client libraries that provide support for RedisAI's commands
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