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Merged
merged 13 commits into from
Sep 4, 2024
Merged

Adds vLLM as Option for Local App #693

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7dbd31d
Update local-apps.ts
EliMCosta May 21, 2024
32560d8
Update packages/tasks/src/local-apps.ts
EliMCosta May 22, 2024
f97747a
Update packages/tasks/src/local-apps.ts
EliMCosta May 22, 2024
82233de
Update local-apps.ts
EliMCosta May 22, 2024
2123430
Validation for `config.quantization_config.quant_method`
julien-c May 22, 2024
43de0e9
Update local-apps.ts
EliMCosta May 22, 2024
8557110
Update packages/tasks/src/local-apps.ts
EliMCosta May 30, 2024
2c3c6c2
Merge branch 'main' into patch-4
krampstudio Sep 2, 2024
17ad182
fix: udpate snippets
krampstudio Sep 3, 2024
2bb1bc1
Update packages/tasks/src/local-apps.ts
krampstudio Sep 4, 2024
d63b7cb
fix: rely only on gguf tag
krampstudio Sep 4, 2024
6fd56ef
Merge branch 'main' into patch-4
krampstudio Sep 4, 2024
0308303
Merge branch 'main' into patch-4
pcuenca Sep 4, 2024
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42 changes: 42 additions & 0 deletions packages/tasks/src/local-apps.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -63,6 +63,41 @@ LLAMA_CURL=1 make
];
};

const snippetVllm = (model: ModelData): string[] => {
return [
`
## Deploy with docker (needs Docker installed) a gated model (please, request access in Hugginface's model repo):
docker run --runtime nvidia --gpus all \
--name my_vllm_container \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HUGGING_FACE_HUB_TOKEN=<secret>" \
-p 8000:8000 \
--ipc=host \
vllm/vllm-openai:latest \
--model ${model.id}
`,
`
## Load and run the model
docker exec -it my_vllm_container bash -c "python -m vllm.entrypoints.openai.api_server --model ${model.id} --dtype auto --api-key token-abc123"
`,
`
## Call the server using the official OpenAI Python client library, or any other HTTP client
from openai import OpenAI
client = OpenAI(
base_url="http://localhost:8000/v1",
api_key="token-abc123",
)
completion = client.chat.completions.create(
model=${model.id},
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(completion.choices[0].message)
`,
];
};

/**
* Add your new local app here.
*
Expand All @@ -82,6 +117,13 @@ export const LOCAL_APPS = {
displayOnModelPage: isGgufModel,
snippet: snippetLlamacpp,
},
"vllm": {
prettyLabel: "vLLM",
docsUrl: "https://docs.vllm.ai",
mainTask: "text-generation",
displayOnModelPage: isGptqModel && isAwqModel,
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how would you define those methods?

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how would you define those methods?

In fact, the suggested vLLM method deploys the non-quantized version from the Hugginface repository. All examples of type "text-generation" in the code are GGUF. Any suggestion?

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Thank you for the PR! Concretely we support a set of architectures which is readable from the model data

huggingface.js/packages/tasks/src/model-data.ts

Line 40 in 04a0eb4

architectures?: string[];

https://github.com/vllm-project/vllm/blob/757b62c49560baa6f294310a53032348a0d95939/vllm/model_executor/models/__init__.py#L13-L63

And for quantization method we can read in config.quantization_config.quant_method which we support awq, gptq, aqlm, and marlin

https://huggingface.co/TheBloke/zephyr-7B-alpha-AWQ/blob/main/config.json#L28

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awesome @simon-mo, super clear!

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@julien-c julien-c May 22, 2024 •
edited
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i've pushed 2123430 on this PR to type config.quantization_config.quant_method which we now parse & pass from the Hub

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i've pushed 2123430 on this PR to type config.quantization_config.quant_method which we now parse & pass from the Hub

I made some changes, I need your help to review

snippet: snippetVllm,
},
lmstudio: {
prettyLabel: "LM Studio",
docsUrl: "https://lmstudio.ai",
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