Instructions to use kernels-community/megablocks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use kernels-community/megablocks with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("kernels-community/megablocks") - Notebooks
- Google Colab
- Kaggle
File size: 985 Bytes
2595c46 1b3fb21 2595c46 1b3fb21 9c4ca75 1b3fb21 9c4ca75 09e15a7 1b3fb21 09e15a7 1b3fb21 09e15a7 1b3fb21 9c4ca75 9193618 1b3fb21 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | ---
library_name: kernels
license: apache-2.0
---
This is the repository card of kernels-community/megablocks that has been pushed on the Hub. It was built to be used with the [`kernels` library](https://github.com/huggingface/kernels). This card was automatically generated.
## How to use
```python
# make sure `kernels` is installed: `pip install -U kernels`
from kernels import get_kernel
kernel_module = get_kernel("kernels-community/megablocks")
MyReplacementLayer = kernel_module.MyReplacementLayer
MyReplacementLayer(...)
```
## Available functions
- `MyReplacementLayer`
- `exclusive_cumsum`
- `inclusive_cumsum`
- `histogram`
- `indices`
- `replicate_forward`
- `replicate_backward`
- `sort`
- `cumsum`
- `argsort`
- `Arguments`
- `ParallelDroplessMLP`
- `dMoE`
- `SparseGLU`
- `MLP`
- `SparseMLP`
- `MoE`
- `ParallelMLP`
- `get_load_balancing_loss`
## Benchmarks
Benchmarking script is available for this kernel. Run `kernels benchmark kernels-community/megablocks`.
|