Comments (7)
Update August 2023:
I kind of dislike containers and usually prefer pure metal, but the below method should work (untested):
Install AMD drivers (may need to chown _apt amd_driver.deb to install), install vim or text editor of choice, enable Universe repositories (basic OS setup)
sudo apt-get update
sudo apt-get upgrade
go through the docker website installation steps (there are more than a few and must be followed perfectly)
Once you have docker:
docker pull rocm/pytorch-nightly
sudo docker run -it --network=host --device=/dev/kfd --device=/dev/dri --group-add=video --ipc=host --cap-add=SYS_PTRACE --security-opt seccomp=unconfined rocm/pytorch-nightly
In the running image:
cd /home
export HSA_OVERRIDE_GFX_VERSION=10.3.0
Install bitsandbytes with ROCM support (optional)
git clone https://github.com/arlo-phoenix/bitsandbytes-rocm-5.6.git bitsandbytes
cd bitsandbytes
make hip ROCM_TARGET=gfx1030
pip install pip --upgrade
pip install .
Install chatrwkv
cd ..
pip install --upgrade git+https://github.com/BlinkDL/ChatRWKV
download the model you want from one of the normal places
echo "alias python3='rocm-smi --setfan 99%;python3' #AMD fan curve was not aggressive enough for my cooling" >> ~/.bashrc
cd ChatRWKV/v2
vim chat.py # edit in your model location and other parameters you care about
python3 chat.py
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bitsandbytes-rocm also is very challenging to get up and running for 8bit on regular transformers (in steps following after the final steps of this guide)
it may be hardcoded for 5.3 rocm at the time of this writing, this means this guide may be incompatible with bitsandbytes-rocm (the github of this project is not an official AMD one and i won't link it here for that reason, easy to find though)
also, a lot of these issues may be resolved by purchasing AMD Machine Learning silicon (such as MI210) instead of consumer cards, but where's the fun in that (also ain't nobody got that kind of money)
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How about wsl2?
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How is the performance?
People has reported that it's around RTX-3070. I am still interested in the performance, especially when using RWKV.
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Wsl 2 does not support AMD ROCM yet at the time of this guide. Please use dual boot methods, or consider switching entirely to Linux (if you can get Proton working for gaming, etc). I would be happy to learn otherwise whenever this changes.
…
On Sat, Mar 18, 2023, 1:12 AM CatUnderCar @.> wrote: How about wsl2? — Reply to this email directly, view it on GitHub <#15 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/AEMUTTV33GTVQWC7RXT7VILW4U72LANCNFSM6AAAAAAVCIQKS4 . You are receiving this because you authored the thread.Message ID: @.>
Thanks
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Related Issues (20)
- 很好的模型,但是 HOT 4
- 求助time-mixing部分,处理数值溢出代码的解释
- Feature Request: an option to use Positional Interpolation to extent CTX length at inference time HOT 2
- Add a support to "stop_words" in PIPELINE
- 开源中文NSFW微调模型
- demo ? HOT 2
- demo true error ? HOT 1
- 'No CUDA GPUs are available' in google colab with V100 GPU and high RAM HOT 2
- huggingface无法访问,模型无法下载 HOT 4
- Prompt for RAG with RWKV-4-World-7B-v1-20230626-ctx4096 HOT 1
- [Feature Request] text2music HOT 2
- RuntimeError: Error building extension 'wkv_cuda_v1' HOT 2
- How to write the RWKV in autogressive style like RNN HOT 2
- NameError: name 'PIPELINE' is not defined HOT 1
- 大哥,乱码了 HOT 1
- 回复总是截断了,如何让回复自然的结束 HOT 1
- eagle-7B HOT 1
- Inference doesn't work on Apple Macbook even when using CPU fp32 as strategy HOT 1
- "cpu fp32i8" strategy not working in RWKV v6 through Python rwkv module HOT 2
- How to run new v5-Eagle-7B HOT 2
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