Restore n_tensor check.
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2 changed files with 7 additions and 3 deletions
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@ -367,6 +367,12 @@ class Model:
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break
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for new_name, data_torch in (self._modify_tensors(data_torch, name, bid)):
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# Some GPTQ models have empty bias tensors which are not in the model architecture.
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# These tensors will cause tensor number check to fail, so we have to skip them.
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if new_name.endswith(".bias") and np.all(LazyTorchTensor.to_eager(data_torch).numpy() == 0):
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logger.info(f"Skipping empty bias tensor: {new_name}")
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continue
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data = data_torch.squeeze().numpy()
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# if data ends up empty, it means data_torch was a scalar tensor -> restore
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@ -4783,9 +4783,7 @@ struct llama_model_loader {
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void done_getting_tensors() const {
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if (n_created != n_tensors) {
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// Zero bias in some HuggingFace models will cause n_tensors mismatch
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// Consider removing zero bias in convert_hf_to_gguf.py?
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// throw std::runtime_error(format("%s: wrong number of tensors; expected %d, got %d", __func__, n_tensors, n_created));
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throw std::runtime_error(format("%s: wrong number of tensors; expected %d, got %d", __func__, n_tensors, n_created));
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}
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}
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