Update docker image path in README (#181)

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Karol Damaszke 2024-07-05 10:29:02 +02:00 committed by GitHub
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@ -31,7 +31,7 @@ To use [🤗 text-generation-inference](https://github.com/huggingface/text-gene
1. Pull the official Docker image with: 1. Pull the official Docker image with:
```bash ```bash
docker pull ghcr.io/huggingface/tgi-gaudi:2.0.0 docker pull ghcr.io/huggingface/tgi-gaudi:2.0.1
``` ```
> [!NOTE] > [!NOTE]
> Alternatively, you can build the Docker image using the `Dockerfile` located in this folder with: > Alternatively, you can build the Docker image using the `Dockerfile` located in this folder with:
@ -45,7 +45,7 @@ To use [🤗 text-generation-inference](https://github.com/huggingface/text-gene
model=meta-llama/Llama-2-7b-hf model=meta-llama/Llama-2-7b-hf
volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run
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 ghcr.io/huggingface/tgi-gaudi:2.0.0 --model-id $model --max-input-tokens 1024 --max-total-tokens 2048 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 ghcr.io/huggingface/tgi-gaudi:2.0.1 --model-id $model --max-input-tokens 1024 --max-total-tokens 2048
``` ```
> For gated models such as [LLama](https://huggingface.co/meta-llama) or [StarCoder](https://huggingface.co/bigcode/starcoder), you will have to pass `-e HUGGING_FACE_HUB_TOKEN=<token>` to the `docker run` command above with a valid Hugging Face Hub read token. > For gated models such as [LLama](https://huggingface.co/meta-llama) or [StarCoder](https://huggingface.co/bigcode/starcoder), you will have to pass `-e HUGGING_FACE_HUB_TOKEN=<token>` to the `docker run` command above with a valid Hugging Face Hub read token.
@ -54,7 +54,7 @@ To use [🤗 text-generation-inference](https://github.com/huggingface/text-gene
model=meta-llama/Llama-2-7b-hf model=meta-llama/Llama-2-7b-hf
volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run
docker run -p 8080:80 -v $volume:/data --runtime=habana -e HABANA_VISIBLE_DEVICES=all -e PT_HPU_LAZY_MODE=0 -e OMPI_MCA_btl_vader_single_copy_mechanism=none --cap-add=sys_nice --ipc=host ghcr.io/huggingface/tgi-gaudi:2.0.0 --model-id $model --max-input-tokens 1024 --max-total-tokens 2048 docker run -p 8080:80 -v $volume:/data --runtime=habana -e HABANA_VISIBLE_DEVICES=all -e PT_HPU_LAZY_MODE=0 -e OMPI_MCA_btl_vader_single_copy_mechanism=none --cap-add=sys_nice --ipc=host ghcr.io/huggingface/tgi-gaudi:2.0.1 --model-id $model --max-input-tokens 1024 --max-total-tokens 2048
``` ```
iii. On 8 Gaudi/Gaudi2 cards: iii. On 8 Gaudi/Gaudi2 cards:
@ -62,7 +62,7 @@ To use [🤗 text-generation-inference](https://github.com/huggingface/text-gene
model=meta-llama/Llama-2-70b-hf model=meta-llama/Llama-2-70b-hf
volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run
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 ghcr.io/huggingface/tgi-gaudi:2.0.0 --model-id $model --sharded true --num-shard 8 --max-input-tokens 1024 --max-total-tokens 2048 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 ghcr.io/huggingface/tgi-gaudi:2.0.1 --model-id $model --sharded true --num-shard 8 --max-input-tokens 1024 --max-total-tokens 2048
``` ```
3. You can then send a simple request: 3. You can then send a simple request:
```bash ```bash
@ -139,7 +139,7 @@ docker run -p 8080:80 \
-e PAD_SEQUENCE_TO_MULTIPLE_OF=128 \ -e PAD_SEQUENCE_TO_MULTIPLE_OF=128 \
--cap-add=sys_nice \ --cap-add=sys_nice \
--ipc=host \ --ipc=host \
ghcr.io/huggingface/tgi-gaudi:2.0.0 \ ghcr.io/huggingface/tgi-gaudi:2.0.1 \
--model-id $model \ --model-id $model \
--max-input-tokens 1024 \ --max-input-tokens 1024 \
--max-batch-prefill-tokens 4096 \ --max-batch-prefill-tokens 4096 \
@ -169,7 +169,7 @@ docker run -p 8080:80 \
-e QUANT_CONFIG=./quantization_config/maxabs_quant.json \ -e QUANT_CONFIG=./quantization_config/maxabs_quant.json \
--cap-add=sys_nice \ --cap-add=sys_nice \
--ipc=host \ --ipc=host \
ghcr.io/huggingface/tgi-gaudi:2.0.0 \ ghcr.io/huggingface/tgi-gaudi:2.0.1 \
--model-id $model \ --model-id $model \
--max-input-tokens 1024 \ --max-input-tokens 1024 \
--max-batch-prefill-tokens 4096 \ --max-batch-prefill-tokens 4096 \
@ -197,7 +197,7 @@ docker run -p 8080:80 \
-e PAD_SEQUENCE_TO_MULTIPLE_OF=128 \ -e PAD_SEQUENCE_TO_MULTIPLE_OF=128 \
--cap-add=sys_nice \ --cap-add=sys_nice \
--ipc=host \ --ipc=host \
ghcr.io/huggingface/tgi-gaudi:2.0.0 \ ghcr.io/huggingface/tgi-gaudi:2.0.1 \
--model-id $model \ --model-id $model \
--max-input-tokens 1024 \ --max-input-tokens 1024 \
--max-batch-prefill-tokens 16384 \ --max-batch-prefill-tokens 16384 \
@ -231,7 +231,7 @@ docker run -p 8080:80 \
-e QUANT_CONFIG=./quantization_config/maxabs_quant.json \ -e QUANT_CONFIG=./quantization_config/maxabs_quant.json \
--cap-add=sys_nice \ --cap-add=sys_nice \
--ipc=host \ --ipc=host \
ghcr.io/huggingface/tgi-gaudi:2.0.0 \ ghcr.io/huggingface/tgi-gaudi:2.0.1 \
--model-id $model \ --model-id $model \
--max-input-tokens 1024 \ --max-input-tokens 1024 \
--max-batch-prefill-tokens 16384 \ --max-batch-prefill-tokens 16384 \