# Following Pytorch init, except scale by 1/sqrt(2 * n_layer) # We need to reinit p since this code could be called multiple times # Having just p *= scale would repeatedly scale it down with torch.no_grad(): p /= math.sqrt(num_residuals_per_layer * self.config.num_hidden...
llama_model_loader: - kv 6: general.tags arr[str,6] = ["facebook","meta","pytorch","llam...llama_model_loader: - kv 7: general.languages arr[str,8] = ["en","de","fr","it","pt","hi", ...llama_model_loader: - kv 8: llama.block_count u32 = 16llama_model_loade...
Steps to reproduce: Run a Docker container using ollama/ollama:rocm on a machine with a single MI300X Inside the container, run ollama run llama3.1:70B Actual behaviour: rocBLAS error: Could not initialize Tensile host: No devices found ...
# https://pytorch.org/docs/stable/torchvision/models.html torchvision.transforms.Normalize( mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225) ), ] ) return image_transform def _build_dataset(self, dataset_key): return HatefulMemesDataset( data_path=self.hparams.get(dataset_key, dataset...