diff --git a/netlify.toml b/netlify.toml
index c116eb49b..45bd2c3b6 100644
--- a/netlify.toml
+++ b/netlify.toml
@@ -48,4 +48,6 @@ redirects = [
     {from = "/api/sentencesegmenter", to="/api/sentencizer"},
     {from = "/universe", to = "/universe/project/:id", query = {id = ":id"}, force = true},
     {from = "/universe", to = "/universe/category/:category", query = {category = ":category"}, force = true},
+    # Renamed universe projects
+    {from = "/universe/project/spacy-pytorch-transformers", to = "/universe/project/spacy-transformers", force = true}
 ]
diff --git a/website/meta/languages.json b/website/meta/languages.json
index 09a17b568..364b2ef6a 100644
--- a/website/meta/languages.json
+++ b/website/meta/languages.json
@@ -8,10 +8,10 @@
                 "en_core_web_md",
                 "en_core_web_lg",
                 "en_vectors_web_lg",
-                "en_pytt_bertbaseuncased_lg",
-                "en_pytt_robertabase_lg",
-                "en_pytt_distilbertbaseuncased_lg",
-                "en_pytt_xlnetbasecased_lg"
+                "en_trf_bertbaseuncased_lg",
+                "en_trf_robertabase_lg",
+                "en_trf_distilbertbaseuncased_lg",
+                "en_trf_xlnetbasecased_lg"
             ],
             "example": "This is a sentence.",
             "has_examples": true
@@ -19,7 +19,7 @@
         {
             "code": "de",
             "name": "German",
-            "models": ["de_core_news_sm", "de_core_news_md", "de_pytt_bertbasecased_lg"],
+            "models": ["de_core_news_sm", "de_core_news_md", "de_trf_bertbasecased_lg"],
             "example": "Dies ist ein Satz.",
             "has_examples": true
         },
diff --git a/website/meta/universe.json b/website/meta/universe.json
index d30b77ca4..47fe27cc4 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -1675,21 +1675,21 @@
             }
         },
         {
-            "id": "spacy-pytorch-transformers",
-            "title": "spacy-pytorch-transformers",
+            "id": "spacy-transformers",
+            "title": "spacy-transformers",
             "slogan": "spaCy pipelines for pretrained BERT, XLNet and GPT-2",
-            "description": "This package provides spaCy model pipelines that wrap [Hugging Face's `pytorch-transformers`](https://github.com/huggingface/pytorch-transformers) package, so you can use them in spaCy. The result is convenient access to state-of-the-art transformer architectures, such as BERT, GPT-2, XLNet, etc.",
-            "github": "explosion/spacy-pytorch-transformers",
-            "url": "https://explosion.ai/blog/spacy-pytorch-transformers",
-            "pip": "spacy-pytorch-transformers",
+            "description": "This package provides spaCy model pipelines that wrap [Hugging Face's `transformers`](https://github.com/huggingface/transformers) package, so you can use them in spaCy. The result is convenient access to state-of-the-art transformer architectures, such as BERT, GPT-2, XLNet, etc.",
+            "github": "explosion/spacy-transformers",
+            "url": "https://explosion.ai/blog/spacy-transformers",
+            "pip": "spacy-transformers",
             "category": ["pipeline", "models", "research"],
             "code_example": [
                 "import spacy",
                 "",
-                "nlp = spacy.load(\"en_pytt_bertbaseuncased_lg\")",
+                "nlp = spacy.load(\"en_trf_bertbaseuncased_lg\")",
                 "doc = nlp(\"Apple shares rose on the news. Apple pie is delicious.\")",
                 "print(doc[0].similarity(doc[7]))",
-                "print(doc._.pytt_last_hidden_state.shape)"
+                "print(doc._.trf_last_hidden_state.shape)"
             ],
             "author": "Explosion",
             "author_links": {
diff --git a/website/src/templates/models.js b/website/src/templates/models.js
index 3ab701727..82c7e4219 100644
--- a/website/src/templates/models.js
+++ b/website/src/templates/models.js
@@ -23,6 +23,7 @@ const MODEL_META = {
     dep: 'Vocabulary, syntax',
     ent: 'Named entities',
     pytt: 'PyTorch Transformers',
+    trf: 'Transformers',
     vectors: 'Word vectors',
     web: 'written text (blogs, news, comments)',
     news: 'written text (news, media)',