Update README.md

Author: FL33TW00D

README.md

@@ -3,35 +3,33 @@
 [![](https://img.shields.io/endpoint?url=https%3A%2F%2Fswiftpackageindex.com%2Fapi%2Fpackages%2Fhuggingface%2Fswift-transformers%2Fbadge%3Ftype%3Dswift-versions)](https://swiftpackageindex.com/huggingface/swift-transformers)
 [![](https://img.shields.io/endpoint?url=https%3A%2F%2Fswiftpackageindex.com%2Fapi%2Fpackages%2Fhuggingface%2Fswift-transformers%2Fbadge%3Ftype%3Dplatforms)](https://swiftpackageindex.com/huggingface/swift-transformers)
 
-This is a collection of utilities to help adopt language models in Swift apps. It tries to follow the Python `transformers` API and abstractions whenever possible, but it also aims to provide an idiomatic Swift interface and does not assume prior familiarity with [`transformers`](https://github.com/huggingface/transformers) or [`tokenizers`](https://github.com/huggingface/tokenizers).
+This is a collection of utilities to help adopt language models in Swift apps. 
 
+It tries to follow the Python `transformers` API and abstractions whenever possible, but it also aims to provide an idiomatic Swift interface and does not assume prior familiarity with [`transformers`](https://github.com/huggingface/transformers) or [`tokenizers`](https://github.com/huggingface/tokenizers).
 
-## Rationale and Overview
 
-Please, check [our post](https://huggingface.co/blog/swift-coreml-llm).
+## Rationale & Overview
 
-## Modules
+Check out [our announcement post](https://huggingface.co/blog/swift-coreml-llm).
 
-- `Tokenizers`. Utilities to convert text to tokens and back. Follows the abstractions in [`tokenizers`](https://github.com/huggingface/tokenizers) and [`transformers.js`](https://github.com/xenova/transformers.js). Usage example:
+## Modules
 
+- `Tokenizers`: Utilities to convert text to tokens and back, with support for Chat Templates and Tools. Follows the abstractions in [`tokenizers`](https://github.com/huggingface/tokenizers). Usage example:
 ```swift
 import Tokenizers
-
 func testTokenizer() async throws {
-    let tokenizer = try await AutoTokenizer.from(pretrained: "pcuenq/Llama-2-7b-chat-coreml")
-    let inputIds = tokenizer("Today she took a train to the West")
-    assert(inputIds == [1, 20628, 1183, 3614, 263, 7945, 304, 278, 3122])
+    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)
 }
 ```
 
-However, you don't usually need to tokenize the input text yourself - the [`Generation` code](https://github.com/huggingface/swift-transformers/blob/17d4bfae3598482fc7ecf1a621aa77ab586d379a/Sources/Generation/Generation.swift#L82) will take care of it.
-
-- `Hub`. Utilities to download configuration files from the Hub, used to instantiate tokenizers and learn about language model characteristics.
-
-- `Generation`. Algorithms for text generation. Currently supported ones are greedy search and top-k sampling.
-
-- `Models`. Language model abstraction over a Core ML package.
+You don't usually need to tokenize the input text yourself - the [`Generation` code](https://github.com/huggingface/swift-transformers/blob/17d4bfae3598482fc7ecf1a621aa77ab586d379a/Sources/Generation/Generation.swift#L82) will take care of it.
 
+- `Hub`: Utilities to download config files from the Hub, used to instantiate tokenizers and learn about language model characteristics.
+- `Generation`: Algorithms for text generation. Currently supported ones are greedy search and top-k sampling.
+- `Models`: Language model abstraction over a Core ML package.
 
 ## Supported Models
 
@@ -45,19 +43,13 @@ This package has been tested with autoregressive language models such as:
 
 Encoder-decoder models such as T5 and Flan are currently _not supported_. They are high up in our [priority list](#roadmap).
 
-## 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).
-- [`transformers-to-coreml`](https://huggingface.co/spaces/coreml-projects/transformers-to-coreml), a no-code Core ML conversion tool built on `exporters`.
-
-## SwiftPM
+## 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: "0.1.5")
+    .package(url: "https://github.com/huggingface/swift-transformers", from: "0.1.17")
 ]
 ```
 
@@ -74,29 +66,11 @@ targets: [
 ]
 ```
 
-## <a name="roadmap"></a> Roadmap / To Do
-
-- [ ] Tokenizers: download from the Hub, port from [`tokenizers`](https://github.com/huggingface/tokenizers)
-  - [x] BPE family
-  - [x] Fix Falcon, broken while porting BPE
-  - [x] Improve tests, add edge cases, see https://github.com/xenova/transformers.js/blob/27920d84831e323275b38f0b5186644b7936e1a2/tests/generate_tests.py#L24
-  - [x] Include fallback `tokenizer_config.json` for known architectures whose models don't have a configuration in the Hub (GPT2)
-  - [ ] Port other tokenizer types: Unigram, WordPiece
-- [ ] [`exporters`](https://github.com/huggingface/exporters) – Core ML conversion tool.
-  - [x] Allow max sequence length to be specified.
-  - [ ] Allow discrete shapes
-  - [x] Return `logits` from converted Core ML model
-  - [x] Use `coremltools` @ `main` for latest fixes. In particular, [this merged PR](https://github.com/apple/coremltools/pull/1915) makes it easier to use recent versions of transformers.
-- [ ] Generation
-  - [ ] Nucleus sampling (we currently have greedy and top-k sampling)
-  - [ ] Use [new `top-k` implementation in `Accelerate`](https://developer.apple.com/documentation/accelerate/bnns#4164142).
-  - [ ] Support discrete shapes in the underlying Core ML model by selecting the smallest sequence length larger than the input.
-- [ ] Optimization: cache past key-values.
-- [ ] Encoder-decoder models (T5)
-- [ ] [Demo app](https://github.com/huggingface/swift-chat)
-  - [ ] Allow system prompt to be specified.
-  - [ ] How to define a system prompt template?
-  - [ ] Test a code model (to stretch system prompt definition)
+## 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).
+- [`transformers-to-coreml`](https://huggingface.co/spaces/coreml-projects/transformers-to-coreml), a no-code Core ML conversion tool built on `exporters`.
 
 ## License