---
license: apache-2.0
pipeline_tag: automatic-speech-recognition
library_name: executorch
---

# whisper-base

This repository hosts the **whisper-base** models exported for the
[React Native ExecuTorch](https://www.npmjs.com/package/react-native-executorch)
library as ExecuTorch `.pte` programs, ready to run on device.

Upstream model: [whisper-base](https://huggingface.co/openai/whisper-base)

## Variants

| Path | Backend | Precision |
| --- | --- | --- |
| `coreml/whisper_base_coreml_fp16.pte` | coreml | fp16 |
| `mlx/whisper_base_mlx_bf16.pte` | mlx | bf16 |
| `mlx/whisper_base_mlx_int8.pte` | mlx | int8 |
| `vulkan/whisper_base_vulkan_fp16.pte` | vulkan | fp16 |
| `vulkan/whisper_base_vulkan_int8.pte` | vulkan | int8 |
| `xnnpack/whisper_base_xnnpack_fp32.pte` | xnnpack | fp32 |
| `xnnpack/whisper_base_xnnpack_int8.pte` | xnnpack | int8 |

## XNNPACK int8

`xnnpack/whisper_base_xnnpack_int8.pte` is 8da8w (int8 dynamic activations, int8
per-channel weights). Greedy WER (CER for zh) against the fp32 file, LibriSpeech
test-clean (150 clips) and FLEURS (80 per language):

| | en | de | es | pl | fr | zh |
| --- | --- | --- | --- | --- | --- | --- |
| fp32 | 4.12 | 24.88 | 13.66 | 47.35 | 40.76 | 21.27 |
| int8 | 3.94 | 25.04 | 13.87 | 46.39 | 41.09 | 21.27 |

## Repository structure

```
config.json                            34 B
coreml/config.json                     1.5 kB
coreml/whisper_base_coreml_fp16.pte    140 MB
mlx/config.json                        2.6 kB
mlx/whisper_base_mlx_bf16.pte          139 MB
mlx/whisper_base_mlx_int8.pte          97.8 MB
tokenizer.json                         2.4 MB
vulkan/config.json                     2.6 kB
vulkan/whisper_base_vulkan_fp16.pte    335 MB
vulkan/whisper_base_vulkan_int8.pte    196 MB
xnnpack/config.json                    2.6 kB
xnnpack/whisper_base_xnnpack_fp32.pte  380 MB
xnnpack/whisper_base_xnnpack_int8.pte  254 MB
```

## Compatibility

These files are published for the **ExecuTorch v1.4.1** runtime. ExecuTorch
gives no forward compatibility guarantee, so an older runtime may fail to load
them.

To use them in React Native ExecuTorch, pass the model constant shipped in the
library's model registry to the corresponding task pipeline. See the
[documentation](https://docs.swmansion.com/react-native-executorch/docs/fundamentals/downloading-models).

To load these files in your own ExecuTorch runtime, read the
[compatibility note](https://github.com/pytorch/executorch/blob/main/runtime/COMPATIBILITY.md)
first.