FBGEMM_GPU
FBGEMM_GPU (FBGEMM GPU Kernels Library) is a collection of high-performance PyTorch GPU operator libraries for training and inference. The library provides efficient table batched embedding bag, data layout transformation, and quantization supports.
See the full Documentation for more information on building, installing, and developing with FBGEMM_GPU, as well as the most up-to-date support matrix for this library.
Join the FBGEMM_GPU Community
For questions, support, news updates, or feature requests, please feel free to:
- File a ticket in GitHub Issues
- Post a discussion in GitHub Discussions
- Reach out to us on the
#fbgemmchannel in PyTorch Slack
For contributions, please see the CONTRIBUTING file for
ways to help out.
License
FBGEMM_GPU is BSD licensed, as found in the LICENSE file.
2 maintainers
Release files for fbgemm-gpu-nightly-cpu 2026.9.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 56.8 MB
Release files / fbgemm_gpu_nightly_cpu-2026.9.3-cp314-cp314-manylinux_2_28_x86_64.whl
| Download URL | fbgemm_gpu_nightly_cpu-2026.9.3-cp314-cp314-manylinux_2_28_x86_64.whl |
|---|---|
| Size | 6.4 MB |
| Tags | CPython 3.14 Linux glibc 2.28+ x86-64 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
|
Release files / fbgemm_gpu_nightly_cpu-2026.9.3-cp314-cp314-manylinux_2_28_aarch64.whl
| Download URL | fbgemm_gpu_nightly_cpu-2026.9.3-cp314-cp314-manylinux_2_28_aarch64.whl |
|---|---|
| Size | 4.9 MB |
| Tags | CPython 3.14 Linux glibc 2.28+ ARM64 |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
|
Release files / fbgemm_gpu_nightly_cpu-2026.9.3-cp313-cp313-manylinux_2_28_x86_64.whl
| Download URL | fbgemm_gpu_nightly_cpu-2026.9.3-cp313-cp313-manylinux_2_28_x86_64.whl |
|---|---|
| Size | 6.4 MB |
| Tags | CPython 3.13 Linux glibc 2.28+ x86-64 |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.13.15
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Release files / fbgemm_gpu_nightly_cpu-2026.9.3-cp313-cp313-manylinux_2_28_aarch64.whl
| Download URL | fbgemm_gpu_nightly_cpu-2026.9.3-cp313-cp313-manylinux_2_28_aarch64.whl |
|---|---|
| Size | 4.9 MB |
| Tags | CPython 3.13 Linux glibc 2.28+ ARM64 |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.13.15
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Release files / fbgemm_gpu_nightly_cpu-2026.9.3-cp312-cp312-manylinux_2_28_x86_64.whl
| Download URL | fbgemm_gpu_nightly_cpu-2026.9.3-cp312-cp312-manylinux_2_28_x86_64.whl |
|---|---|
| Size | 6.4 MB |
| Tags | CPython 3.12 Linux glibc 2.28+ x86-64 |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.12.14
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Release files / fbgemm_gpu_nightly_cpu-2026.9.3-cp312-cp312-manylinux_2_28_aarch64.whl
| Download URL | fbgemm_gpu_nightly_cpu-2026.9.3-cp312-cp312-manylinux_2_28_aarch64.whl |
|---|---|
| Size | 4.9 MB |
| Tags | CPython 3.12 Linux glibc 2.28+ ARM64 |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.12.14
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Release files / fbgemm_gpu_nightly_cpu-2026.9.3-cp311-cp311-manylinux_2_28_x86_64.whl
| Download URL | fbgemm_gpu_nightly_cpu-2026.9.3-cp311-cp311-manylinux_2_28_x86_64.whl |
|---|---|
| Size | 6.4 MB |
| Tags | CPython 3.11 Linux glibc 2.28+ x86-64 |
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No |
| Uploaded via |
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Release files / fbgemm_gpu_nightly_cpu-2026.9.3-cp311-cp311-manylinux_2_28_aarch64.whl
| Download URL | fbgemm_gpu_nightly_cpu-2026.9.3-cp311-cp311-manylinux_2_28_aarch64.whl |
|---|---|
| Size | 4.9 MB |
| Tags | CPython 3.11 Linux glibc 2.28+ ARM64 |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.11.16
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Release files / fbgemm_gpu_nightly_cpu-2026.9.3-cp310-cp310-manylinux_2_28_x86_64.whl
| Download URL | fbgemm_gpu_nightly_cpu-2026.9.3-cp310-cp310-manylinux_2_28_x86_64.whl |
|---|---|
| Size | 6.4 MB |
| Tags | CPython 3.10 Linux glibc 2.28+ x86-64 |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.10.21
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Release files / fbgemm_gpu_nightly_cpu-2026.9.3-cp310-cp310-manylinux_2_28_aarch64.whl
| Download URL | fbgemm_gpu_nightly_cpu-2026.9.3-cp310-cp310-manylinux_2_28_aarch64.whl |
|---|---|
| Size | 4.9 MB |
| Tags | CPython 3.10 Linux glibc 2.28+ ARM64 |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.10.21
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