https://github.com/huggingface/swift-transformers
Swift Package to implement a transformers-like API in Swift
https://github.com/huggingface/swift-transformers
Last synced: 3 months ago
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Swift Package to implement a transformers-like API in Swift
- Host: GitHub
- URL: https://github.com/huggingface/swift-transformers
- Owner: huggingface
- License: apache-2.0
- Created: 2023-05-11T10:56:48.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-09-23T16:46:14.000Z (4 months ago)
- Last Synced: 2025-09-23T18:09:27.608Z (4 months ago)
- Language: Swift
- Size: 5.04 MB
- Stars: 1,103
- Watchers: 30
- Forks: 137
- Open Issues: 21
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
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`swift-transformers` is a collection of utilities to help adopt language models in Swift apps.
Those familiar with the [`transformers`](https://github.com/huggingface/transformers) Python library will find a familiar yet idiomatic Swift API.
## Rationale & Overview
Check out [our v1.0 release post](https://huggingfce.co/blog/swift-transformers) and our [original announcement](https://huggingface.co/blog/swift-coreml-llm) for more context on why we built this library.
## Examples
The most commonly used modules from `swift-transformers` are `Tokenizers` and `Hub`, which allow fast tokenization and
model downloads from the Hugging Face Hub.
### Tokenizing text + chat templating
Tokenizing text should feel very familiar to those who have used the Python `transformers` library:
```swift
let tokenizer = try await AutoTokenizer.from(pretrained: "deepseek-ai/DeepSeek-R1-Distill-Qwen-7B")
let messages = [["role": "user", "content": "Describe the Swift programming language."]]
let encoded = try tokenizer.applyChatTemplate(messages: messages)
let decoded = tokenizer.decode(tokens: encoded)
```
### Tool calling
`swift-transformers` natively supports formatting inputs for tool calling, allowing for complex interactions with language models:
```swift
let tokenizer = try await AutoTokenizer.from(pretrained: "mlx-community/Qwen2.5-7B-Instruct-4bit")
let weatherTool = [
"type": "function",
"function": [
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": [
"type": "object",
"properties": ["location": ["type": "string", "description": "City and state"]],
"required": ["location"]
]
]
]
let tokens = try tokenizer.applyChatTemplate(
messages: [["role": "user", "content": "What's the weather in Paris?"]],
tools: [weatherTool]
)
```
### Hub downloads
Downloading models to a user device _fast_ and _reliably_ is a core requirement of on-device ML. `swift-transformers` provides a simple API to
download models from the Hugging Face Hub, with progress reporting, flaky connection handling, and more:
```swift
let repo = Hub.Repo(id: "mlx-community/Qwen2.5-0.5B-Instruct-2bit-mlx")
let modelDirectory: URL = try await Hub.snapshot(
from: repo,
matching: ["config.json", "*.safetensors"],
progressHandler: { progress in
print("Download progress: \(progress.fractionCompleted * 100)%")
}
)
print("Files downloaded to: \(modelDirectory.path)")
```
### CoreML Integration
The `Models` and `Generation` modules provide handy utilities when working with language models in CoreML. Check out our
example converting and running Mistral 7B using CoreML [here](https://github.com/huggingface/swift-transformers/tree/main/Examples).
The [modernization of Core ML](https://github.com/huggingface/swift-transformers/pull/257) and corresponding examples were primarily contributed by @joshnewnham, @1duo, @alejandro-isaza, @aseemw. Thank you 🙏
## Usage via SwiftPM
To use `swift-transformers` with SwiftPM, you can add this to your `Package.swift`:
```swift
dependencies: [
.package(url: "https://github.com/huggingface/swift-transformers", from: "0.1.17")
]
```
And then, add the Transformers library as a dependency to your target:
```swift
targets: [
.target(
name: "YourTargetName",
dependencies: [
.product(name: "Transformers", package: "swift-transformers")
]
)
]
```
## Projects that use swift-transformers ❤️
- [WhisperKit](https://github.com/argmaxinc/WhisperKit): A Swift Package for state-of-the-art speech-to-text systems from [Argmax](https://github.com/argmaxinc)
- [MLX Swift Examples](https://github.com/ml-explore/mlx-swift-examples): A Swift Package for integrating MLX models in Swift apps.
Using `swift-transformers` in your project? Let us know and we'll add you to the list!
## Other Tools
- [`swift-chat`](https://github.com/huggingface/swift-chat), a simple app demonstrating how to use this package.
- [`exporters`](https://github.com/huggingface/exporters), a Core ML conversion package for transformers models, based on Apple's [`coremltools`](https://github.com/apple/coremltools).
## Contributing
Swift Transformers is a community project and we welcome contributions. Please
check out [Issues](https://github.com/huggingface/swift-transformers/issues)
tagged with `good first issue` if you are looking for a place to start!
Before submitting a pull request, please ensure your code:
- Passes the test suite (`swift test`)
- Passes linting checks (`swift format lint --recursive .`)
To format your code, run `swift format -i --recursive .`.
## License
[Apache 2](LICENSE).