fix: weights_only=False for SelVA checkpoints (PyTorch 2.6 compat)
PyTorch 2.6 changed the default to weights_only=True. SelVA checkpoints contain non-tensor types (numpy scalars etc.) that fail strict unpickling. All weights come from trusted sources (jnwnlee/selva HF repo). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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@@ -57,7 +57,7 @@ class FeaturesUtils(nn.Module):
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self.synchformer = Synchformer(video=True, audio=False)
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self.synchformer.load_state_dict(
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torch.load(synchformer_ckpt, weights_only=True, map_location='cpu'))
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torch.load(synchformer_ckpt, weights_only=False, map_location='cpu'))
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self.text_encoder_t5 = T5EncoderModel.from_pretrained('google/flan-t5-base')
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self.tokenizer_t5 = T5TokenizerFast.from_pretrained('google/flan-t5-base')
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