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# Text Generation Inference on Habana Gaudi | ||
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To use [🤗 text-generation-inference](https://github.com/huggingface/text-generation-inference) on Habana Gaudi/Gaudi2, follow these steps: | ||
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1. Build the Docker image located in this folder with: | ||
```bash | ||
docker build -t tgi_gaudi . | ||
``` | ||
2. Launch a local server instance on 1 Gaudi card: | ||
```bash | ||
model=meta-llama/Llama-2-7b-hf | ||
volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run | ||
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docker run -p 8080:80 -v $volume:/data --runtime=habana -e HABANA_VISIBLE_DEVICES=all -e OMPI_MCA_btl_vader_single_copy_mechanism=none --cap-add=sys_nice --ipc=host tgi_gaudi --model-id $model | ||
``` | ||
3. Launch a local server instance on 8 Gaudi cards: | ||
```bash | ||
model=meta-llama/Llama-2-70b-hf | ||
volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run | ||
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docker run -p 8080:80 -v $volume:/data --runtime=habana -e PT_HPU_ENABLE_LAZY_COLLECTIVES=true -e HABANA_VISIBLE_DEVICES=all -e OMPI_MCA_btl_vader_single_copy_mechanism=none --cap-add=sys_nice --ipc=host tgi_gaudi --model-id $model --sharded true --num-shard 8 | ||
``` | ||
4. You can then send a request: | ||
```bash | ||
curl 127.0.0.1:8080/generate \ | ||
-X POST \ | ||
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}' \ | ||
-H 'Content-Type: application/json' | ||
``` | ||
> The first call will be slower as the model is compiled. | ||
5. To run benchmark test, please refer [TGI's benchmark tool](https://github.com/huggingface/text-generation-inference/tree/main/benchmark). | ||
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To run it on the same machine, you can do the following: | ||
* `docker exec -it <docker name> bash` , pick the docker started from step 3 or 4 using docker ps | ||
* `text-generation-benchmark -t <model-id>` , pass the model-id from docker run command | ||
* after the completion of tests, hit ctrl+c to see the performance data summary. | ||
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> For gated models such as [StarCoder](https://huggingface.co/bigcode/starcoder), you will have to pass `-e HUGGING_FACE_HUB_TOKEN=<token>` to the `docker run` command above with a valid Hugging Face Hub read token. | ||
For more information and documentation about Text Generation Inference, checkout [the README](https://github.com/huggingface/text-generation-inference#text-generation-inference) of the original repo. | ||
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Not all features of TGI are currently supported as this is still a work in progress. | ||
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New changes are added for the current release: | ||
- Sharded feature with support for DeepSpeed-inference auto tensor parallism. Also use HPU graph for performance improvement. | ||
- Torch profile. | ||
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Enviroment Variables Added: | ||
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<div align="center"> | ||
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| Name | Value(s) | Default | Description | Usage | | ||
|------------------ |:---------------|:------------|:-------------------- |:--------------------------------- | ||
| MAX_TOTAL_TOKENS | integer | 0 | Control the padding of input | add -e in docker run, such | | ||
| ENABLE_HPU_GRAPH | true/false | true | Enable hpu graph or not | add -e in docker run command | | ||
| PROF_WARMUPSTEP | integer | 0 | Enable/disable profile, control profile warmup step, 0 means disable profile | add -e in docker run command | | ||
| PROF_STEP | interger | 5 | Control profile step | add -e in docker run command | | ||
| PROF_PATH | string | /root/text-generation-inference | Define profile folder | add -e in docker run command | | ||
| LIMIT_HPU_GRAPH | True/False | False | Skip HPU graph usage for prefill to save memory | add -e in docker run command | | ||
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</div> | ||
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> The license to use TGI on Habana Gaudi is the one of TGI: https://github.com/huggingface/text-generation-inference/blob/main/LICENSE | ||
> | ||
> Please reach out to [email protected] if you have any question. | ||
Please refer to the following fork of TGI for deploying it on Habana Gaudi: https://github.com/huggingface/tgi-gaudi |
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