Fixed links in the README.

Author: umarbutler

CHANGELOG.md

@@ -1,6 +1,10 @@
 ## Changelog 🔄
 All notable changes to `semchunk` will be documented here. This project adheres to [Keep a Changelog](https://keepachangelog.com/en/1.1.0/) and [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.1.1] - 2023-11-07
+### Fixed
+- Fixed links in the README.
+
 ## [0.1.1] - 2023-11-07
 ### Added
 - Added new test samples.

README.md

@@ -3,7 +3,7 @@
 
 `semchunk` is a fast and lightweight pure Python library for splitting text into semantically meaningful chunks.
 
-Owing to its complex yet highly efficient chunking algorithm, `semchunk` is both more semantically accurate than [`langchain.text_splitter.RecursiveCharacterTextSplitter`](https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/recursive_text_splitter) (see [How It Works 🔍](#how-it-works-)) and is also over 60% faster than [`semantic-text-splitter`](https://pypi.org/project/semantic-text-splitter/) (see the [Benchmarks 📊](#benchmarks-)).
+Owing to its complex yet highly efficient chunking algorithm, `semchunk` is both more semantically accurate than [`langchain.text_splitter.RecursiveCharacterTextSplitter`](https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/recursive_text_splitter) (see [How It Works 🔍](https://github.com/umarbutler/semchunk#how-it-works-)) and is also over 60% faster than [`semantic-text-splitter`](https://pypi.org/project/semantic-text-splitter/) (see the [Benchmarks 📊](https://github.com/umarbutler/semchunk#benchmarks-)).
 
 ## Installation 📦
 `semchunk` may be installed with `pip`:
@@ -63,7 +63,7 @@ To ensure that chunks are as semantically meaningful as possible, `semchunk` use
 ## Benchmarks 📊
 On a desktop with a Ryzen 3600, 64 GB of RAM, Windows 11 and Python 3.12.0, it takes `semchunk` 35.75 seconds to split every sample in [NLTK's Gutenberg Corpus](https://www.nltk.org/howto/corpus.html#plaintext-corpora) into 512-token-long chunks (for context, the Corpus contains 18 texts and 3,001,260 tokens). By comparison, it takes [`semantic-text-splitter`](https://pypi.org/project/semantic-text-splitter/) 1 minute and 50.5 seconds to chunk the same texts into 512-token-long chunks — a difference of 67.65%.
 
-The code used to benchmark `semchunk` and `semantic-text-splitter` is available [here](tests/bench.py).
+The code used to benchmark `semchunk` and `semantic-text-splitter` is available [here](https://github.com/umarbutler/semchunk/blob/main/tests/bench.py).
 
 ## Licence 📄
-This library is licensed under the [MIT License](https://github.com/umarbutler/semchunk/blob/main/LICENSE).
+This library is licensed under the [MIT License](https://github.com/umarbutler/semchunk/blob/main/LICENCE).

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "semchunk"
-version = "0.1.1"
+version = "0.1.2"
 authors = [
   {name="Umar Butler", email="[email protected]"},
 ]