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Author:
vLLM Team
Summary:
A high-throughput and memory-efficient inference and serving engine for LLMs
Latest version:
0.12.0
Required dependencies:
aiohttp
|
anthropic
|
blake3
|
cachetools
|
cbor2
|
cloudpickle
|
compressed-tensors
|
depyf
|
diskcache
|
einops
|
fastapi
|
filelock
|
flashinfer-python
|
gguf
|
lark
|
llguidance
|
lm-format-enforcer
|
mistral_common
|
model-hosting-container-standards
|
msgspec
|
ninja
|
numba
|
numpy
|
openai
|
openai-harmony
|
opencv-python-headless
|
outlines_core
|
partial-json-parser
|
pillow
|
prometheus-fastapi-instrumentator
|
prometheus_client
|
protobuf
|
psutil
|
py-cpuinfo
|
pybase64
|
pydantic
|
python-json-logger
|
pyyaml
|
pyzmq
|
ray
|
regex
|
requests
|
scipy
|
sentencepiece
|
setproctitle
|
setuptools
|
six
|
tiktoken
|
tokenizers
|
torch
|
torchaudio
|
torchvision
|
tqdm
|
transformers
|
typing_extensions
|
watchfiles
|
xgrammar
Optional dependencies:
datasets
|
fastsafetensors
|
librosa
|
matplotlib
|
mistral_common
|
pandas
|
petit-kernel
|
runai-model-streamer
|
seaborn
|
soundfile
|
tensorizer
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