diff --git a/CHANGELOG.md b/CHANGELOG.md
index 0f8dfda..92f059b 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,13 +1,16 @@
 # Changelog
 All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 
-## [Unreleased]
+## [0.18.0] - 2022-07-24
 ## Added
 - Support for sentence embeddings models and pipelines, based on [SentenceTransformers](https://www.sbert.net).
 
 ## Changed
 - Upgraded to `torch` 1.12 (via `tch` 0.8.0)
 
+## Fixed
+- Allow empty slices or slices of empty prompts for text generation.
+
 ## [0.18.0] - 2022-05-29
 ## Added
 - Addition of the DeBERTa language model and support for question answering, sequence and token classification
diff --git a/Cargo.toml b/Cargo.toml
index 1ddc8e2..b94031b 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "rust-bert"
-version = "0.18.0"
+version = "0.19.0"
 authors = ["Guillaume Becquin <guillaume.becquin@gmail.com>"]
 edition = "2018"
 description = "Ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)"
@@ -65,22 +65,22 @@ features = ["doc-only"]
 [dependencies]
 rust_tokenizers = "~7.0.2"
 tch = "~0.8.0"
-serde_json = "1.0.81"
-serde = { version = "1.0.137", features = ["derive"] }
+serde_json = "1.0.82"
+serde = { version = "1.0.140", features = ["derive"] }
 ordered-float = "3.0.0"
-uuid = { version = "1.1.0", features = ["v4"] }
+uuid = { version = "1.1.2", features = ["v4"] }
 thiserror = "1.0.31"
-half = "1.8.2"
+half = "2.1.0"
 
 cached-path = { version = "0.5.3", optional = true }
 dirs = { version = "4.0.0", optional = true }
 lazy_static = { version = "1.4.0", optional = true }
 
 [dev-dependencies]
-anyhow = "1.0.57"
+anyhow = "1.0.58"
 csv = "1.1.6"
-criterion = "0.3.5"
-tokio = { version = "1.18.2", features = ["sync", "rt-multi-thread", "macros"] }
+criterion = "0.3.6"
+tokio = { version = "1.20.0", features = ["sync", "rt-multi-thread", "macros"] }
 torch-sys =  "~0.8.0"
 tempfile = "3.3.0"
 itertools = "0.10.3"
diff --git a/README.md b/README.md
index edfbfd0..9839cbe 100644
--- a/README.md
+++ b/README.md
@@ -32,35 +32,36 @@ The tasks currently supported include:
   - Named Entity Recognition
   - Part of Speech tagging
   - Question-Answering
-  - Language Generation.
+  - Language Generation
+  - Sentence Embeddings
 
 <details>
 <summary> <b>Expand to display the supported models/tasks matrix </b> </summary>
 
-| |**Sequence classification**|**Token classification**|**Question answering**|**Text Generation**|**Summarization**|**Translation**|**Masked LM**|
-:-----:|:----:|:----:|:-----:|:----:|:-----:|:----:|:----:
-DistilBERT|✅|✅|✅| | | |✅| 
-MobileBERT|✅|✅|✅| | | |✅| 
-DeBERTa|✅|✅|✅| | | |✅| 
-DeBERTa (v2)|✅|✅|✅| | | |✅| 
-FNet|✅|✅|✅| | | |✅| 
-BERT|✅|✅|✅| | | |✅| 
-RoBERTa|✅|✅|✅| | | |✅| 
-GPT| | | |✅ | | | | 
-GPT2| | | |✅ | | | | 
-GPT-Neo| | | |✅ | | | | 
-BART|✅| | |✅ |✅| | |
-Marian| | | |  | |✅| | 
-MBart|✅| | |✅ | | | | 
-M2M100| | | |✅ | | | | 
-Electra | |✅| | | | |✅| 
-ALBERT |✅|✅|✅| | | |✅| 
-T5 | | | |✅ |✅|✅| | 
-XLNet|✅|✅|✅|✅ | | |✅| 
-Reformer|✅| |✅|✅ | | |✅| 
-ProphetNet| | | |✅ |✅ | | | 
-Longformer|✅|✅|✅| | | |✅| 
-Pegasus| | | | |✅| | | 
+| |**Sequence classification**|**Token classification**|**Question answering**|**Text Generation**|**Summarization**|**Translation**|**Masked LM**|**Sentence Embeddings**|
+:-----:|:----:|:----:|:-----:|:----:|:-----:|:----:|:----:|:----:
+DistilBERT|✅|✅|✅| | | |✅| ✅| 
+MobileBERT|✅|✅|✅| | | |✅| |
+DeBERTa|✅|✅|✅| | | |✅| |
+DeBERTa (v2)|✅|✅|✅| | | |✅| |
+FNet|✅|✅|✅| | | |✅| |
+BERT|✅|✅|✅| | | |✅| ✅|
+RoBERTa|✅|✅|✅| | | |✅| ✅| 
+GPT| | | |✅ | | | |  |
+GPT2| | | |✅ | | | |  |
+GPT-Neo| | | |✅ | | | | | 
+BART|✅| | |✅ |✅| | | |
+Marian| | | |  | |✅| |  |
+MBart|✅| | |✅ | | | |  |
+M2M100| | | |✅ | | | |  |
+Electra | |✅| | | | |✅|  |
+ALBERT |✅|✅|✅| | | |✅| ✅ |
+T5 | | | |✅ |✅|✅| | ✅ |
+XLNet|✅|✅|✅|✅ | | |✅|  |
+Reformer|✅| |✅|✅ | | |✅|  |
+ProphetNet| | | |✅ |✅ | | |  |
+Longformer|✅|✅|✅| | | |✅|  |
+Pegasus| | | | |✅| | |  |
 </details>
 
 ## Getting started
@@ -379,6 +380,31 @@ Output:
 ]
 ```
 </details>
+&nbsp;  
+<details>
+<summary> <b>10. Sentence embeddings </b> </summary>
+
+Generate sentence embeddings (vector representation). These can be used for applications including dense information retrieval.
+```rust
+    let model = SentenceEmbeddingsBuilder::remote(
+            SentenceEmbeddingsModelType::AllMiniLmL12V2
+        ).create_model()?;
+
+    let sentences = [
+        "this is an example sentence", 
+        "each sentence is converted"
+    ];
+    
+    let output = model.predict(&sentences);
+```
+Output:
+```
+[
+    [-0.000202666, 0.08148022, 0.03136178, 0.002920636 ...],
+    [0.064757116, 0.048519745, -0.01786038, -0.0479775 ...]
+]
+```
+</details>
 
 ## Benchmarks
 
diff --git a/examples/sentence_embeddings_local.rs b/examples/sentence_embeddings_local.rs
index f148f94..f4d43d0 100644
--- a/examples/sentence_embeddings_local.rs
+++ b/examples/sentence_embeddings_local.rs
@@ -21,7 +21,6 @@ use rust_bert::pipelines::sentence_embeddings::SentenceEmbeddingsBuilder;
 /// ```sh
 ///   python ../utils/convert_model.py  resources/path/to/2_Dense/pytorch_model.bin --suffix
 /// ```
-///
 fn main() -> anyhow::Result<()> {
     // Set-up sentence embeddings model
     let model = SentenceEmbeddingsBuilder::local("resources/all-MiniLM-L12-v2")
diff --git a/src/lib.rs b/src/lib.rs
index f7b1938..5fee123 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -39,7 +39,8 @@
 //! - Named Entity Recognition
 //! - Part of Speech tagging
 //! - Question-Answering
-//! - Language Generation.
+//! - Language Generation
+//! - Sentence Embeddings
 //!
 //! More information on these can be found in the [`pipelines` module](./pipelines/index.html)
 //! - Transformer models base architectures with customized heads. These allow to load pre-trained models for customized inference in Rust
@@ -47,30 +48,30 @@
 //! <details>
 //! <summary> <b> Click to expand to display the supported models/tasks matrix </b> </summary>
 //!
-//! | |**Sequence classification**|**Token classification**|**Question answering**|**Text Generation**|**Summarization**|**Translation**|**Masked LM**|
-//! :-----:|:----:|:----:|:-----:|:----:|:-----:|:----:|:----:
-//! DistilBERT|✅|✅|✅| | | |✅|
-//! MobileBERT|✅|✅|✅| | | |✅|
-//! DeBERTa|✅|✅|✅| | | |✅|
-//! DeBERTa (v2)|✅|✅|✅| | | |✅|
-//! FNet|✅|✅|✅| | | |✅|
-//! BERT|✅|✅|✅| | | |✅|
-//! RoBERTa|✅|✅|✅| | | |✅|
-//! GPT| | | |✅ | | | |
-//! GPT2| | | |✅ | | | |
-//! GPT-Neo| | | |✅ | | | |
-//! BART|✅| | |✅ |✅| | |
-//! Marian| | | |  | |✅| |
-//! MBart|✅| | |✅ | | | |
-//! M2M100| | | |✅ | | | |
-//! Electra | |✅| | | | |✅|
-//! ALBERT |✅|✅|✅| | | |✅|
-//! T5 | | | |✅ |✅|✅| |
-//! XLNet|✅|✅|✅|✅ | | |✅|
-//! Reformer|✅| |✅|✅ | | |✅|
-//! ProphetNet| | | |✅ |✅ | | |
-//! Longformer|✅|✅|✅| | | |✅|
-//! Pegasus| | | | |✅| | |
+//!| |**Sequence classification**|**Token classification**|**Question answering**|**Text Generation**|**Summarization**|**Translation**|**Masked LM**|**Sentence Embeddings**|
+//!:-----:|:----:|:----:|:-----:|:----:|:-----:|:----:|:----:|:----:
+//!DistilBERT|✅|✅|✅| | | |✅| ✅|
+//!MobileBERT|✅|✅|✅| | | |✅| |
+//!DeBERTa|✅|✅|✅| | | |✅| |
+//!DeBERTa (v2)|✅|✅|✅| | | |✅| |
+//!FNet|✅|✅|✅| | | |✅| |
+//!BERT|✅|✅|✅| | | |✅| ✅|
+//!RoBERTa|✅|✅|✅| | | |✅| ✅|
+//!GPT| | | |✅ | | | |  |
+//!GPT2| | | |✅ | | | |  |
+//!GPT-Neo| | | |✅ | | | | |
+//!BART|✅| | |✅ |✅| | | |
+//!Marian| | | |  | |✅| |  |
+//!MBart|✅| | |✅ | | | |  |
+//!M2M100| | | |✅ | | | |  |
+//!Electra | |✅| | | | |✅|  |
+//!ALBERT |✅|✅|✅| | | |✅| ✅ |
+//!T5 | | | |✅ |✅|✅| | ✅ |
+//!XLNet|✅|✅|✅|✅ | | |✅|  |
+//!Reformer|✅| |✅|✅ | | |✅|  |
+//!ProphetNet| | | |✅ |✅ | | |  |
+//!Longformer|✅|✅|✅| | | |✅|  |
+//!Pegasus| | | | |✅| | |  |
 //! </details>
 //!
 //! # Getting started
@@ -84,8 +85,8 @@
 //!
 //! ### Manual installation (recommended)
 //!
-//! 1. Download `libtorch` from <https://pytorch.org/get-started/locally/>. This package requires `v1.10.0`: if this version is no longer available on the "get started" page,
-//! the file should be accessible by modifying the target link, for example `https://download.pytorch.org/libtorch/cu111/libtorch-shared-with-deps-1.10.0%2Bcu111.zip` for a Linux version with CUDA11.
+//! 1. Download `libtorch` from <https://pytorch.org/get-started/locally/>. This package requires `v1.12.0`: if this version is no longer available on the "get started" page,
+//! the file should be accessible by modifying the target link, for example `https://download.pytorch.org/libtorch/cu116/libtorch-cxx11-abi-shared-with-deps-1.12.0%2Bcu116.zip` for a Linux version with CUDA11.
 //! 2. Extract the library to a location of your choice
 //! 3. Set the following environment variables
 //! ##### Linux:
@@ -103,7 +104,7 @@
 //! ### Automatic installation
 //!
 //! Alternatively, you can let the `build` script automatically download the `libtorch` library for you.
-//! The CPU version of libtorch will be downloaded by default. To download a CUDA version, please set the environment variable `TORCH_CUDA_VERSION` to `cu111`.
+//! The CPU version of libtorch will be downloaded by default. To download a CUDA version, please set the environment variable `TORCH_CUDA_VERSION` to `cu116`.
 //! Note that the libtorch library is large (order of several GBs for the CUDA-enabled version) and the first build may therefore take several minutes to complete.
 //!
 //! # Ready-to-use pipelines
@@ -544,7 +545,36 @@
 //! ]
 //! # ;
 //! ```
+//! </details>
+//! &nbsp;  
+//! <details>
+//! <summary> <b>10. Sentence embeddings </b> </summary>
 //!
+//! Generate sentence embeddings (vector representation). These can be used for applications including dense information retrieval.
+//!```no_run
+//! # use rust_bert::pipelines::sentence_embeddings::{SentenceEmbeddingsBuilder, SentenceEmbeddingsModelType};
+//! # fn main() -> anyhow::Result<()> {
+//!    let model = SentenceEmbeddingsBuilder::remote(
+//!             SentenceEmbeddingsModelType::AllMiniLmL12V2
+//!         ).create_model()?;
+//!
+//!     let sentences = [
+//!         "this is an example sentence",
+//!         "each sentence is converted"
+//!     ];
+//!     
+//!     let output = model.predict(&sentences);
+//! # }
+//! ```
+//! Output:
+//! ```no_run
+//! # let output =
+//! [
+//!     [-0.000202666, 0.08148022, 0.03136178, 0.002920636],
+//!     [0.064757116, 0.048519745, -0.01786038, -0.0479775],
+//! ]
+//! # ;
+//! ```
 //! </details>
 //!
 //! ## Benchmarks
diff --git a/src/pipelines/mod.rs b/src/pipelines/mod.rs
index 002453f..864a711 100644
--- a/src/pipelines/mod.rs
+++ b/src/pipelines/mod.rs
@@ -409,6 +409,34 @@
 //! ]
 //! # ;
 //! ```
+//!
+//! #### 10. Sentence embeddings
+//!
+//! Generate sentence embeddings (vector representation). These can be used for applications including dense information retrieval.
+//!```no_run
+//! # use rust_bert::pipelines::sentence_embeddings::{SentenceEmbeddingsBuilder, SentenceEmbeddingsModelType};
+//! # fn main() -> anyhow::Result<()> {
+//!    let model = SentenceEmbeddingsBuilder::remote(
+//!             SentenceEmbeddingsModelType::AllMiniLmL12V2
+//!         ).create_model()?;
+//!
+//!     let sentences = [
+//!         "this is an example sentence",
+//!         "each sentence is converted"
+//!     ];
+//!     
+//!     let output = model.predict(&sentences);
+//! # }
+//! ```
+//! Output:
+//! ```no_run
+//! # let output =
+//! [
+//!     [-0.000202666, 0.08148022, 0.03136178, 0.002920636],
+//!     [0.064757116, 0.048519745, -0.01786038, -0.0479775],
+//! ]
+//! # ;
+//! ```
 
 pub mod common;
 pub mod conversation;
diff --git a/tests/longformer.rs b/tests/longformer.rs
index 0a61bfe..dc235a1 100644
--- a/tests/longformer.rs
+++ b/tests/longformer.rs
@@ -309,7 +309,7 @@ fn longformer_for_multiple_choice() -> anyhow::Result<()> {
 }
 
 #[test]
-fn mobilebert_for_token_classification() -> anyhow::Result<()> {
+fn longformer_for_token_classification() -> anyhow::Result<()> {
     //    Resources paths
     let config_resource =
         RemoteResource::from_pretrained(LongformerConfigResources::LONGFORMER_BASE_4096);