Comments (2)
LoganDark
commented on May 31, 2024
5
I have uploaded some quantized RWKV-4-Raven models to HuggingFace at LoganDark/rwkv-4-raven-ggml. Conversion took about 2 hours, and upload took about 24 hours and 500GB of disk space.
At the time of writing, the available models are:
| Name | f32 |
f16 |
Q4_0 |
Q4_1 |
Q4_2 |
Q5_1 |
Q8_0 |
|---|---|---|---|---|---|---|---|
RWKV-4-Raven-1B5-v11-Eng99-20230425-ctx4096 |
Yes | Yes | Yes | No | Yes | Yes | Yes |
RWKV-4-Raven-3B-v11-Eng99-20230425-ctx4096 |
Yes | Yes | Yes | No | Yes | Yes | Yes |
RWKV-4-Raven-7B-v11x-Eng99-20230429-ctx8192 |
Yes | Yes | Yes | No | Yes | Yes | Yes |
RWKV-4-Raven-14B-v11x-Eng99-20230501-ctx8192 |
Split | Yes | Yes | No | Yes | Yes | Yes |
Feel free to create a discussion if you have a request.
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saharNooby
commented on May 31, 2024
Only PyTorch -> rwkv.cpp conversion would require to load the whole model in the RAM; quantization is done tensor-by-tensor. You are right about the bandwidth tho.
I'll consider it, thanks for the suggestion!
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Related Issues (20)
- Tutorial for python script? HOT 1
- Repetitive, meaningless tokens output HOT 3
- it seems does not support the newly RWKV-4-World-CHNtuned-3B-v1-20230625-ctx4096.bin HOT 2
- Can't build with ggml HOT 3
- Support hipBLAS
- Support Metal in apple macOS?
- [QUESTION] Implementing RNN/LSTM with ggml HOT 4
- crash on GGML_ASSERT: 'rwkv.cpp/ggml/src/ggml.c:5316: ggml_can_repeat_rows(b, a)' HOT 1
- Update new GGML for GGML_MAX_NODES limit? HOT 2
- Support RWKV v5 HOT 1
- llama-node is not working in the moment HOT 1
- Fix extras/CMakeList.txt file for static build
- Support build with cublas and hipblas on github action HOT 3
- CMake Error HOT 1
- hipblas cannot build using cmake on windows with rocm5.7.1 HOT 2
- The linked Huging Face page in the README doesn't have any .bin files HOT 1
- Add mac ARM build as part of the build process
- Replace all assertions in Python code with if statements HOT 7
- Support RWKV v6
- Colab notebook to start faster?
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