Comments (13)
joebradly
commented on August 12, 2024
2
I change line 272 to the following:
if (output_ids[0, -keyword_id.shape[0] :, None] == keyword_id).all(): return True
Then the inference runs through.
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Efficient-Large-Language-Model
commented on August 12, 2024
1
For VILA1.5-40B, you should use --conv-mode hermes-2
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Lyken17
commented on August 12, 2024
could @joebradly @SeanCraven314 share your environemnt? The code runs without error on myside.
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SeanCraven314
commented on August 12, 2024
Hi this is a dump of my environment,
I am launching from the cli:
python llava/eval/run_vila.py \
--model-path=Efficient-Large-Model/Llama-3-VILA1.5-8B \
--image-file=test.jpg\
--query "What is this?"
Pip list
accelerate 0.27.2
aiofiles 23.2.1
aiohttp 3.9.5
aiosignal 1.3.1
altair 5.3.0
anyio 4.3.0
async-timeout 4.0.3
attrs 23.2.0
av 12.0.0
bitsandbytes 0.41.0
braceexpand 0.1.7
certifi 2024.2.2
charset-normalizer 3.3.2
click 8.1.7
cmake 3.29.2
contourpy 1.2.1
cycler 0.12.1
datasets 2.16.1
decord 0.6.0
dill 0.3.7
distro 1.9.0
dnspython 2.6.1
einops 0.6.1
einops-exts 0.0.4
email_validator 2.1.1
et-xmlfile 1.1.0
exceptiongroup 1.2.1
fastapi 0.111.0
fastapi-cli 0.0.2
ffmpy 0.3.2
filelock 3.14.0
flash-attn 2.4.2
fonttools 4.51.0
frozenlist 1.4.1
fsspec 2023.10.0
fvcore 0.1.5.post20221221
gradio 3.35.2
gradio_client 0.2.9
h11 0.14.0
hf_transfer 0.1.6
httpcore 0.17.3
httptools 0.6.1
httpx 0.24.0
huggingface-hub 0.23.0
idna 3.7
iopath 0.1.10
Jinja2 3.1.4
joblib 1.4.2
jsonschema 4.22.0
jsonschema-specifications 2023.12.1
kiwisolver 1.4.5
linkify-it-py 2.0.3
lit 18.1.4
markdown-it-py 2.2.0
markdown2 2.4.13
MarkupSafe 2.1.5
matplotlib 3.8.4
mdit-py-plugins 0.3.3
mdurl 0.1.2
mpmath 1.3.0
multidict 6.0.5
multiprocess 0.70.15
networkx 3.3
ninja 1.11.1.1
nltk 3.3
numpy 1.26.4
nvidia-cublas-cu11 11.10.3.66
nvidia-cublas-cu12 12.1.3.1
nvidia-cuda-cupti-cu11 11.7.101
nvidia-cuda-cupti-cu12 12.1.105
nvidia-cuda-nvrtc-cu11 11.7.99
nvidia-cuda-nvrtc-cu12 12.1.105
nvidia-cuda-runtime-cu11 11.7.99
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu11 8.5.0.96
nvidia-cudnn-cu12 8.9.2.26
nvidia-cufft-cu11 10.9.0.58
nvidia-cufft-cu12 11.0.2.54
nvidia-curand-cu11 10.2.10.91
nvidia-curand-cu12 10.3.2.106
nvidia-cusolver-cu11 11.4.0.1
nvidia-cusolver-cu12 11.4.5.107
nvidia-cusparse-cu11 11.7.4.91
nvidia-cusparse-cu12 12.1.0.106
nvidia-nccl-cu11 2.14.3
nvidia-nccl-cu12 2.20.5
nvidia-nvjitlink-cu12 12.4.127
nvidia-nvtx-cu11 11.7.91
nvidia-nvtx-cu12 12.1.105
openai 1.8.0
opencv-python 4.8.0.74
openpyxl 3.1.2
orjson 3.10.3
packaging 24.0
pandas 2.2.2
parameterized 0.9.0
peft 0.5.0
pillow 10.3.0
pip 24.0
portalocker 2.8.2
psutil 5.9.8
pyarrow 16.0.0
pyarrow-hotfix 0.6
pydantic 1.10.15
pydub 0.25.1
Pygments 2.18.0
pyparsing 3.1.2
python-dateutil 2.9.0.post0
python-dotenv 1.0.1
python-multipart 0.0.9
pytorchvideo 0.1.5
pytz 2024.1
pywsd 1.2.4
PyYAML 6.0.1
referencing 0.35.1
regex 2024.4.28
requests 2.31.0
rich 13.7.1
rpds-py 0.18.1
s2wrapper 0.1
safetensors 0.4.3
scikit-learn 1.2.2
scipy 1.13.0
semantic-version 2.10.0
sentencepiece 0.1.99
setuptools 68.2.2
shellingham 1.5.4
shortuuid 1.0.13
six 1.16.0
sniffio 1.3.1
starlette 0.37.2
svgwrite 1.4.3
sympy 1.12
tabulate 0.9.0
termcolor 2.4.0
threadpoolctl 3.5.0
timm 0.9.12
tokenizers 0.15.2
tomli 2.0.1
toolz 0.12.1
torch 2.0.1
torchvision 0.15.2
tqdm 4.66.4
transformers 4.36.2
triton 2.0.0
typer 0.12.3
typing_extensions 4.11.0
tzdata 2024.1
uc-micro-py 1.0.3
ujson 5.9.0
urllib3 2.2.1
uvicorn 0.29.0
uvloop 0.19.0
vila 1.0.0 /home/sean-craven/VILA
watchfiles 0.21.0
wavedrom 2.0.3.post3
webdataset 0.2.86
websockets 12.0
wheel 0.43.0
wn 0.9.5
xxhash 3.4.1
yacs 0.1.8
yarl 1.9.4
Running on intel and A100 on Ubuntu 22.04
from vila.
joebradly
commented on August 12, 2024
could @joebradly @SeanCraven314 share your environemnt? The code runs without error on myside.
Package Version Editable project location
accelerate 0.27.2
aiofiles 23.2.1
aiohttp 3.9.5
aiosignal 1.3.1
altair 5.3.0
anyio 4.3.0
async-timeout 4.0.3
attrs 23.2.0
av 12.0.0
bitsandbytes 0.41.0
braceexpand 0.1.7
certifi 2024.2.2
charset-normalizer 3.3.2
click 8.1.7
cmake 3.29.2
contourpy 1.2.1
cycler 0.12.1
datasets 2.16.1
decord 0.6.0
dill 0.3.7
distro 1.9.0
dnspython 2.6.1
einops 0.6.1
einops-exts 0.0.4
email_validator 2.1.1
et-xmlfile 1.1.0
exceptiongroup 1.2.1
fastapi 0.111.0
fastapi-cli 0.0.2
ffmpy 0.3.2
filelock 3.14.0
flash-attn 2.4.2
fonttools 4.51.0
frozenlist 1.4.1
fsspec 2023.10.0
fvcore 0.1.5.post20221221
gradio 3.35.2
gradio_client 0.2.9
h11 0.14.0
httpcore 0.17.3
httptools 0.6.1
httpx 0.24.0
huggingface-hub 0.23.0
idna 3.7
iopath 0.1.10
Jinja2 3.1.4
joblib 1.4.2
jsonschema 4.22.0
jsonschema-specifications 2023.12.1
kiwisolver 1.4.5
linkify-it-py 2.0.3
lit 18.1.4
markdown-it-py 2.2.0
markdown2 2.4.13
MarkupSafe 2.1.5
matplotlib 3.8.4
mdit-py-plugins 0.3.3
mdurl 0.1.2
mpmath 1.3.0
multidict 6.0.5
multiprocess 0.70.15
networkx 3.3
ninja 1.11.1.1
nltk 3.3
numpy 1.26.4
nvidia-cublas-cu11 11.10.3.66
nvidia-cublas-cu12 12.1.3.1
nvidia-cuda-cupti-cu11 11.7.101
nvidia-cuda-cupti-cu12 12.1.105
nvidia-cuda-nvrtc-cu11 11.7.99
nvidia-cuda-nvrtc-cu12 12.1.105
nvidia-cuda-runtime-cu11 11.7.99
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu11 8.5.0.96
nvidia-cudnn-cu12 8.9.2.26
nvidia-cufft-cu11 10.9.0.58
nvidia-cufft-cu12 11.0.2.54
nvidia-curand-cu11 10.2.10.91
nvidia-curand-cu12 10.3.2.106
nvidia-cusolver-cu11 11.4.0.1
nvidia-cusolver-cu12 11.4.5.107
nvidia-cusparse-cu11 11.7.4.91
nvidia-cusparse-cu12 12.1.0.106
nvidia-nccl-cu11 2.14.3
nvidia-nccl-cu12 2.20.5
nvidia-nvjitlink-cu12 12.4.127
nvidia-nvtx-cu11 11.7.91
nvidia-nvtx-cu12 12.1.105
openai 1.8.0
opencv-python 4.8.0.74
openpyxl 3.1.2
orjson 3.10.3
packaging 24.0
pandas 2.2.2
parameterized 0.9.0
peft 0.5.0
pillow 10.3.0
pip 24.0
portalocker 2.8.2
psutil 5.9.8
pyarrow 16.0.0
pyarrow-hotfix 0.6
pydantic 1.10.15
pydub 0.25.1
Pygments 2.18.0
pyparsing 3.1.2
python-dateutil 2.9.0.post0
python-dotenv 1.0.1
python-multipart 0.0.9
pytorchvideo 0.1.5
pytz 2024.1
pywsd 1.2.4
PyYAML 6.0.1
referencing 0.35.1
regex 2024.4.28
requests 2.31.0
rich 13.7.1
rpds-py 0.18.0
s2wrapper 0.1
safetensors 0.4.3
scikit-learn 1.2.2
scipy 1.13.0
semantic-version 2.10.0
sentencepiece 0.1.99
setuptools 69.5.1
shellingham 1.5.4
shortuuid 1.0.13
six 1.16.0
sniffio 1.3.1
starlette 0.37.2
svgwrite 1.4.3
sympy 1.12
tabulate 0.9.0
termcolor 2.4.0
threadpoolctl 3.5.0
timm 0.9.12
tokenizers 0.15.2
tomli 2.0.1
toolz 0.12.1
torch 2.0.1
torchvision 0.15.2
tqdm 4.66.4
transformers 4.36.2
triton 2.0.0
typer 0.12.3
typing_extensions 4.11.0
tzdata 2024.1
uc-micro-py 1.0.3
ujson 5.9.0
urllib3 2.2.1
uvicorn 0.29.0
uvloop 0.19.0
vila 1.0.0 /home/deping.zhang/code/llm/VILA
watchfiles 0.21.0
wavedrom 2.0.3.post3
webdataset 0.2.86
websockets 12.0
wheel 0.43.0
wn 0.9.5
xxhash 3.4.1
yacs 0.1.8
yarl 1.9.4
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gaodianzhuo
commented on August 12, 2024
感谢楼上
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Efficient-Large-Language-Model
commented on August 12, 2024
Will verify and fix.
BTW, you need to use --conv-mode=llama_3 w/ llama3 model.
from vila.
Efficient-Large-Language-Model
commented on August 12, 2024
It seems when using the correct conv mode, there is no issue. Therefore, no code change is needed.
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SeanCraven314
commented on August 12, 2024
Thanks very much for this. Sorry for the hassle.
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hkunzhe
commented on August 12, 2024
It seems when using the correct conv mode, there is no issue. Therefore, no code change is needed.
Hi, run_vila.py with VILA1.5-40B (not llama-3) will encounter the same issue. Use the workaround from @joebradly will fix it.
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Stevetich
commented on August 12, 2024
For VILA1.5-40B, you should use
--conv-mode hermes-2
Hi, I am curious about the setting of the conv_mode, will different conv_mode setting have a very big influence?
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Efficient-Large-Language-Model
commented on August 12, 2024
Yes, the model is trained w/ those conv_mode, in theory, we should bake this parameter into the model config and don't let user change it.
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Lyken17
commented on August 12, 2024
Different conv_mode will lead to different conversation template. In our next release, we will improve this and make this a built-in feature of models so the users do not need change it by themselves.
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