fix: Restore PyTorch 2.11 compatibility for torch.hub and checkpoint loading

PyTorch 2.11.0 changed the default for trust_repo in torch.hub.load()
from None to "check", which raises an error in non-interactive CI
environments. Pass trust_repo=True explicitly in torch.hub tests.

Also explicitly pass weights_only=False to load_state_dict_from_url and
torch.load since our checkpoints contain config dicts alongside weights.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: jamt9000

.github/workflows/pyright.yml

@@ -15,7 +15,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: '3.11'
+          python-version: '3.13'
 
       - name: Install dependencies
         run: |

detoxify/detoxify.py

@@ -38,9 +38,9 @@ def get_model_and_tokenizer(
 def load_checkpoint(model_type="original", checkpoint=None, device="cpu", huggingface_config_path=None):
     if checkpoint is None:
         checkpoint_path = MODEL_URLS[model_type]
-        loaded = torch.hub.load_state_dict_from_url(checkpoint_path, map_location=device)
+        loaded = torch.hub.load_state_dict_from_url(checkpoint_path, map_location=device, weights_only=False)
     else:
-        loaded = torch.load(checkpoint, map_location=device)
+        loaded = torch.load(checkpoint, map_location=device, weights_only=False)
         if "config" not in loaded or "state_dict" not in loaded:
             raise ValueError(
                 "Checkpoint needs to contain the config it was trained \

tests/test_torch_hub.py

@@ -4,22 +4,22 @@
 
 
 def test_torch_hub_models():
-    result = torch.hub.list("unitaryai/detoxify", skip_validation=True)
+    result = torch.hub.list("unitaryai/detoxify", skip_validation=True, trust_repo=True)
 
 
 def test_torch_hub_bert():
-    model = torch.hub.load("unitaryai/detoxify", "toxic_bert", skip_validation=True)
+    model = torch.hub.load("unitaryai/detoxify", "toxic_bert", skip_validation=True, trust_repo=True)
     del model
     gc.collect()
 
 
 def test_torch_hub_roberta():
-    model = torch.hub.load("unitaryai/detoxify", "unbiased_toxic_roberta", skip_validation=True)
+    model = torch.hub.load("unitaryai/detoxify", "unbiased_toxic_roberta", skip_validation=True, trust_repo=True)
     del model
     gc.collect()
 
 
 def test_torch_hub_multilingual():
-    model = torch.hub.load("unitaryai/detoxify", "multilingual_toxic_xlm_r", skip_validation=True)
+    model = torch.hub.load("unitaryai/detoxify", "multilingual_toxic_xlm_r", skip_validation=True, trust_repo=True)
     del model
     gc.collect()