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Running Xinference with Docker? / 是否使用 Docker 运行 Xinfernece?
docker / docker
pip install / 通过 pip install 安装
installation from source / 从源码安装
Version info / 版本信息
0.13.3
The command used to start Xinference / 用以启动 xinference 的命令
xinference-local -H 0.0.0.0
Reproduction / 复现过程
Server error: 400 - [address=0.0.0.0:43423, pid=200222] Couldn't instantiate the backend tokenizer from one of: (1) a 'tokenizers' library serialization file, (2) a slow tokenizer instance to convert or (3) an equivalent slow tokenizer class to instantiate and convert. You need to have sentencepiece installed to convert a slow tokenizer to a fast one.
Expected behavior / 期待表现
llama-3.1-instruct模型正常启动
The text was updated successfully, but these errors were encountered:
System Info / 系統信息
Distributor ID: Ubuntu
Description: Ubuntu 22.04.4 LTS
Python 3.11.8
Cuda compilation tools, release 12.1, V12.1.105
Build cuda_12.1.r12.1/compiler.32688072_0
transformers 4.43.3
Package Version
absl-py 2.1.0
accelerate 0.31.0
addict 2.4.0
aiobotocore 2.7.0
aiofiles 23.2.1
aiohttp 3.9.5
aioitertools 0.11.0
aioprometheus 23.12.0
aiosignal 1.3.1
alembic 1.13.2
aliyun-python-sdk-core 2.15.1
aliyun-python-sdk-kms 2.16.3
altair 5.3.0
annotated-types 0.7.0
anthropic 0.28.0
antlr4-python3-runtime 4.9.3
anyio 4.4.0
argon2-cffi 23.1.0
argon2-cffi-bindings 21.2.0
arrow 1.3.0
asttokens 2.4.1
async-lru 2.0.4
async-timeout 4.0.3
attrdict 2.0.1
attrs 23.2.0
audioread 3.0.1
auto_gptq 0.7.1
autoawq 0.2.5
autoawq_kernels 0.0.6
autopage 0.5.2
Babel 2.15.0
bcrypt 4.1.3
beautifulsoup4 4.12.3
bibtexparser 2.0.0b7
bitsandbytes 0.43.1
bleach 6.1.0
boto3 1.28.64
botocore 1.31.64
cdifflib 1.2.6
certifi 2024.6.2
cffi 1.16.0
cfgv 3.4.0
charset-normalizer 3.3.2
chatglm-cpp 0.3.2
chattts 0.1.1
click 8.1.7
cliff 4.7.0
clldutils 3.22.2
cloudpickle 3.0.0
cmaes 0.10.0
cmake 3.29.5
cmd2 2.4.3
colorama 0.4.6
coloredlogs 15.0.1
colorlog 6.8.2
comm 0.2.2
conformer 0.3.2
contourpy 1.2.1
controlnet-aux 0.0.7
crcmod 1.7
cryptography 42.0.8
csvw 3.3.0
cycler 0.12.1
Cython 3.0.10
datasets 2.18.0
debugpy 1.8.2
decorator 5.1.1
defusedxml 0.7.1
diffusers 0.25.0
dill 0.3.8
diskcache 5.6.3
distlib 0.3.8
distro 1.9.0
dlinfo 1.2.1
dnspython 2.6.1
ecdsa 0.19.0
editdistance 0.8.1
einops 0.8.0
einx 0.2.2
email_validator 2.1.1
encodec 0.1.1
executing 2.0.1
fastapi 0.110.3
fastapi-cli 0.0.4
fastjsonschema 2.20.0
ffmpy 0.3.2
filelock 3.14.0
FlagEmbedding 1.2.10
flatbuffers 24.3.25
fonttools 4.53.0
fqdn 1.5.1
frozendict 2.4.4
frozenlist 1.4.1
fsspec 2023.10.0
gast 0.5.4
gdown 5.2.0
gekko 1.1.1
gradio 4.26.0
gradio_client 0.15.1
greenlet 3.0.3
grpcio 1.65.1
h11 0.14.0
hf_transfer 0.1.6
hiredis 2.3.2
httpcore 1.0.5
httptools 0.6.1
httpx 0.27.0
huggingface-hub 0.23.3
humanfriendly 10.0
hydra-colorlog 1.2.0
hydra-core 1.3.2
hydra-optuna-sweeper 1.2.0
HyperPyYAML 1.2.2
identify 2.6.0
idna 3.7
imageio 2.34.1
importlib_metadata 7.1.0
importlib_resources 6.4.0
inflect 7.2.1
iniconfig 2.0.0
interegular 0.3.3
ipykernel 6.29.5
ipython 8.26.0
ipywidgets 8.1.3
isodate 0.6.1
isoduration 20.11.0
jedi 0.19.1
Jinja2 3.1.4
jiter 0.4.1
jmespath 0.10.0
joblib 1.4.2
json5 0.9.25
jsonpointer 3.0.0
jsonschema 4.22.0
jsonschema-specifications 2023.12.1
jupyter_client 8.6.2
jupyter_core 5.7.2
jupyter-events 0.10.0
jupyter-lsp 2.2.5
jupyter_server 2.14.2
jupyter_server_terminals 0.5.3
jupyterlab 4.2.4
jupyterlab_pygments 0.3.0
jupyterlab_server 2.27.3
jupyterlab_widgets 3.0.11
kiwisolver 1.4.5
language-tags 1.2.0
lark 1.1.9
lazy_loader 0.4
libnacl 2.1.0
librosa 0.10.2.post1
lightning 2.3.3
lightning-utilities 0.11.6
litellm 1.40.15
llama_cpp_python 0.2.77
llvmlite 0.42.0
lm-format-enforcer 0.10.1
lxml 5.2.2
Mako 1.3.5
Markdown 3.6
markdown-it-py 3.0.0
MarkupSafe 2.1.5
matcha-tts 0.0.5.1
matplotlib 3.9.0
matplotlib-inline 0.1.7
mdurl 0.1.2
mistune 3.0.2
modelscope 1.15.0
more-itertools 10.2.0
mpmath 1.3.0
msgpack 1.0.8
multidict 6.0.5
multiprocess 0.70.16
nbclient 0.10.0
nbconvert 7.16.4
nbformat 5.10.4
nemo_text_processing 1.0.2
nest-asyncio 1.6.0
networkx 3.3
ninja 1.11.1.1
nodeenv 1.9.1
notebook 7.2.1
notebook_shim 0.2.4
numba 0.59.1
numpy 1.26.4
nvidia-cublas-cu12 12.1.3.1
nvidia-cuda-cupti-cu12 12.1.105
nvidia-cuda-nvrtc-cu12 12.1.105
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu12 8.9.2.26
nvidia-cufft-cu12 11.0.2.54
nvidia-curand-cu12 10.3.2.106
nvidia-cusolver-cu12 11.4.5.107
nvidia-cusparse-cu12 12.1.0.106
nvidia-ml-py 12.555.43
nvidia-nccl-cu12 2.20.5
nvidia-nvjitlink-cu12 12.5.40
nvidia-nvtx-cu12 12.1.105
omegaconf 2.3.0
onnxruntime 1.16.0
openai 1.33.0
openai-whisper 20231117
opencv-contrib-python 4.10.0.82
opencv-python 4.10.0.82
opencv-python-headless 4.10.0.82
optimum 1.21.2
optuna 2.10.1
orjson 3.10.3
oss2 2.18.5
outlines 0.0.34
overrides 7.7.0
packaging 24.1
pandas 2.2.2
pandocfilters 1.5.1
parso 0.8.4
passlib 1.7.4
pbr 6.0.0
peft 0.11.1
pexpect 4.9.0
phonemizer 3.2.1
pillow 10.3.0
pip 24.2
pip-review 1.3.0
piper-phonemize 1.1.0
platformdirs 4.2.2
pluggy 1.5.0
plumbum 1.8.3
pooch 1.8.2
pre-commit 3.7.1
prettytable 3.10.2
prometheus_client 0.20.0
prometheus-fastapi-instrumentator 7.0.0
prompt_toolkit 3.0.47
protobuf 4.25.4
psutil 5.9.8
ptyprocess 0.7.0
pure_eval 0.2.3
py-cpuinfo 9.0.0
pyarrow 16.1.0
pyarrow-hotfix 0.6
pyasn1 0.6.0
pybase16384 0.3.7
pycparser 2.22
pycryptodome 3.20.0
pydantic 2.7.3
pydantic_core 2.18.4
pydub 0.25.1
Pygments 2.18.0
pylatexenc 2.10
pynini 2.1.5
pynvml 11.5.0
pyparsing 3.1.2
pyperclip 1.9.0
PySocks 1.7.1
pytest 8.3.2
python-dateutil 2.9.0.post0
python-dotenv 1.0.1
python-jose 3.3.0
python-json-logger 2.0.7
python-multipart 0.0.9
pytorch-lightning 2.3.3
pytz 2024.1
PyYAML 6.0.1
pyzmq 26.0.3
quantile-python 1.1
ray 2.24.0
rdflib 7.0.0
redis 5.0.7
referencing 0.35.1
regex 2024.5.15
requests 2.32.3
rfc3339-validator 0.1.4
rfc3986 1.5.0
rfc3986-validator 0.1.1
rich 13.7.1
rootutils 1.0.7
rouge 1.0.1
rpds-py 0.18.1
rpyc 6.0.0
rsa 4.9
ruamel.yaml 0.18.6
ruamel.yaml.clib 0.2.8
ruff 0.4.8
s3fs 2023.10.0
s3transfer 0.7.0
sacremoses 0.1.1
safetensors 0.4.3
scikit-image 0.23.2
scikit-learn 1.5.0
scipy 1.13.1
seaborn 0.13.2
segments 2.2.1
semantic-version 2.10.0
Send2Trash 1.8.3
sentence-transformers 3.0.1
sentencepiece 0.2.0
setuptools 70.0.0
sglang 0.1.17
shellingham 1.5.4
simplejson 3.19.2
six 1.16.0
sniffio 1.3.1
socksio 1.0.0
sortedcontainers 2.4.0
soundfile 0.12.1
soupsieve 2.5
soxr 0.3.7
SQLAlchemy 2.0.31
sse-starlette 2.1.0
stack-data 0.6.3
starlette 0.37.2
stevedore 5.2.0
sympy 1.12.1
tabulate 0.9.0
tblib 3.0.0
tensorboard 2.17.0
tensorboard-data-server 0.7.2
tensorizer 2.9.0
terminado 0.18.1
threadpoolctl 3.5.0
tifffile 2024.5.22
tiktoken 0.7.0
timm 1.0.3
tinycss2 1.3.0
tokenizers 0.19.1
tomli 2.0.1
tomlkit 0.12.0
toolz 0.12.1
torch 2.3.0
torchaudio 2.3.0
torchmetrics 1.4.0.post0
torchvision 0.18.0
tornado 6.4.1
tqdm 4.66.4
traitlets 5.14.3
transformers 4.43.3
transformers-stream-generator 0.0.5
triton 2.3.0
typeguard 4.3.0
typer 0.11.1
types-python-dateutil 2.9.0.20240316
typing_extensions 4.12.2
tzdata 2024.1
ujson 5.10.0
Unidecode 1.3.8
uri-template 1.3.0
uritemplate 4.1.1
urllib3 2.0.7
uvicorn 0.30.1
uvloop 0.19.0
vector-quantize-pytorch 1.14.24
virtualenv 20.26.3
vllm 0.4.3
vllm-flash-attn 2.5.8.post2
vocos 0.1.0
watchfiles 0.22.0
wcwidth 0.2.13
webcolors 24.6.0
webencodings 0.5.1
websocket-client 1.8.0
websockets 11.0.3
Werkzeug 3.0.3
WeTextProcessing 1.0.1
wget 3.2
wheel 0.43.0
widgetsnbextension 4.0.11
wrapt 1.16.0
xformers 0.0.26.post1
xinference 0.13.3
xoscar 0.3.0
xxhash 3.4.1
yapf 0.40.2
yarl 1.9.4
zipp 3.19.2
zmq 0.0.0
zstandard 0.22.0
Running Xinference with Docker? / 是否使用 Docker 运行 Xinfernece?
Version info / 版本信息
0.13.3
The command used to start Xinference / 用以启动 xinference 的命令
xinference-local -H 0.0.0.0
Reproduction / 复现过程
Server error: 400 - [address=0.0.0.0:43423, pid=200222] Couldn't instantiate the backend tokenizer from one of: (1) a 'tokenizers' library serialization file, (2) a slow tokenizer instance to convert or (3) an equivalent slow tokenizer class to instantiate and convert. You need to have sentencepiece installed to convert a slow tokenizer to a fast one.
Expected behavior / 期待表现
llama-3.1-instruct模型正常启动
The text was updated successfully, but these errors were encountered: