Comments (5)
@fibulwinter is correct, the problem was GPU not being available during "docker build". Building the extension when running the container works fine.
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CUDA is not available on Docker build time without tricks: https://discuss.huggingface.co/t/how-to-deal-with-no-gpu-during-docker-build-time/28544
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I finally built a copy of this repo. Here was my setup.
-
docker pull nvidia/cuda:11.7.1-devel-ubuntu22.04
(Must be 11.7) -
Start it up then using Nvidia-docker
-
Run
apt update && apt upgrade -y apt install software-properties-common -y add-apt-repository ppa:deadsnakes/ppa apt install python3.10 -y apt install python3-pip -y
-
pip3 install torch
-
Run
cd llama_model python3 setup_cuda.py install
from gptq-for-llama.
I finally built a copy of this repo. Here was my setup.
docker pull nvidia/cuda:11.7.1-devel-ubuntu22.04
(Must be 11.7)- Start it up then using Nvidia-docker
- Run
apt update && apt upgrade -y apt install software-properties-common -y add-apt-repository ppa:deadsnakes/ppa apt install python3.10 -y apt install python3-pip -y
pip3 install torch
- Run
cd llama_model python3 setup_cuda.py install
Was all that part of docker build, or did some parts happen in docker run / exec?
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Hey @TheTerrasque , I was just testing to find the correct config, so I didn't put it in a Dockerfile. I just ran them manually using bash cli. You can definitely put them within the Dockerfile though.
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Related Issues (20)
- llama_inference 4bits error
- inference with the saved model error: AttributeError: module 'torch.backends.cuda' has no attribute 'sdp_kernel' HOT 2
- Could not obtain official perplexity using bloom_eval()
- can it support openllama model?
- Issue with GPTQ HOT 1
- High PPL when groupsize != -1 for OPT model after replace linear layer with quantlinear. HOT 1
- Help: Quantized llama-7b model with custom prompt format produces only gibberish HOT 1
- Why does the model quantization prompt KILLED at the end? HOT 2
- Would GPTQ be able to support LLaMa2? HOT 1
- Can i quantize HF version of llama model
- Transformers broke again (AttributeError: 'GPTQ' object has no attribute 'inp1') HOT 1
- LoRa and diff with bitsandbytes
- neox.py needs to add "import math"
- error: block with no terminator, has llvm.cond_br %5624, ^bb2, ^bb3
- Support Mistral.
- Syntax changed in triton.testing.do_bench() causing error when running llama_inference.py
- datasets.utils.info_utils.ExpectedMoreSplits: {'validation'} HOT 1
- Error when load GPTQ model
- GPTQ vs bitsandbytes
- add support for minicpm
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