Instructions to use replicate/finegrained-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use replicate/finegrained-fp8 with Kernels:
# !pip install kernels from kernels import get_kernel # a version (or an explicit revision) is required; see the "Files and versions" tab for the available ones kernel = get_kernel("replicate/finegrained-fp8", version=1) - Notebooks
- Google Colab
- Kaggle
File size: 1,032 Bytes
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library_name: kernels
license: apache-2.0
---
> [!CAUTION]
> Starting from September 13, 2026, we will be removing the "model" type repositories of kernels (e.g., kernels-community/flash-attn3). Make sure you're using a latest version of kernels. If you face any disruption, please report them here: https://github.com/huggingface/kernels/issues/new.
This is the repository card of kernels-community/finegrained-fp8 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/finegrained-fp8", version=4)
fp8_act_quant = kernel_module.fp8_act_quant
fp8_act_quant(...)
```
## Available functions
- `fp8_act_quant`
- `matmul_2d`
- `matmul_batched`
- `matmul_grouped`
- `moe_fused_batched`
- `moe_fused_grouped`
## Benchmarks
No benchmark available yet.
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