From 0a210a62e7ffbd32ba766502093159434d0105f0 Mon Sep 17 00:00:00 2001
From: Abdul Fatir Ansari <ansarnd@amazon.com>
Date: Fri, 17 May 2024 15:29:19 +0200
Subject: [PATCH] bump version

---
 README.md      | 1 +
 pyproject.toml | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 96e6da27..2c6651a1 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,7 @@
 
 ## 🚀 News
 
+- **17 May 2024**: 🐛 Fixed an off-by-one error in bin indices in the `output_transform`. This simple fix significantly improves the overall performance of Chronos. We will update the results in the next revision on ArXiv.
 - **10 May 2024**: 🚀 We added the code for pretraining and fine-tuning Chronos models. You can find it in [this folder](./scripts/training). We also added [a script](./scripts/kernel-synth.py) for generating synthetic time series data from Gaussian processes (KernelSynth; see Section 4.2 in the paper for details). Check out the [usage examples](./scripts/).
 - **19 Apr 2024**: 🚀 Chronos is now supported on [AutoGluon-TimeSeries](https://auto.gluon.ai/stable/tutorials/timeseries/index.html), the powerful AutoML package for time series forecasting which enables model ensembles, cloud deployments, and much more. Get started with the [tutorial](https://auto.gluon.ai/stable/tutorials/timeseries/forecasting-chronos.html).
 - **08 Apr 2024**: 🧪 Experimental [MLX inference support](https://github.com/amazon-science/chronos-forecasting/tree/mlx) added. If you have an Apple Silicon Mac, you can now obtain significantly faster forecasts from Chronos compared to CPU inference. This provides an alternative way to exploit the GPU on your Apple Silicon Macs together with the "mps" support in PyTorch.
diff --git a/pyproject.toml b/pyproject.toml
index 15f914e2..28c096b3 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "chronos"
-version = "1.1.0"
+version = "1.2.0"
 requires-python = ">=3.8"
 license = { file = "LICENSE" }
 dependencies = [