" inputs = tokenizer(texts, max_length=128, padding=\"max_length\", truncation=True, return_tensors=\"pt\")\n", " inputs[\"labels\"] = torch.tensor(labels)\n", " return inputs" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "...
inputs = tokenizer(texts, max_length=128, padding="max_length", truncation=True, return_tensors="pt") inputs["labels"] = torch.tensor(labels) return inputs # %% from torch.utils.data import DataLoader from torch.utils.data.distributed import DistributedSampler trainloader = DataLoader(trainse...
ooh ... it's like this, you change the component to xx-ser-net-htl, enter an internal memo saying something like "hi colleagues, could you please fix the time-out error...", choose the "forward" button, choose RCSC Asia, and then save...
"node_modules/@bochilteam/scraper-texts": { "version": "1.0.2", "resolved": "https://registry.npmjs.org/@bochilteam/scraper-texts/-/scraper-texts-1.0.2.tgz", "integrity": "sha512-FRtQlZoOZQv4u5zc4J1w+wnaHLcRnWppQ0zSHvxqqHPSOzH/2M/rt1mfobAMdYGqlV6+ZWjDJrZLeKmM4Kl7XA==",...
inputs = tokenizer(texts, max_length=128, padding="max_length", truncation=True, return_tensors="pt") inputs["labels"] = torch.tensor(labels) return inputstrainloader = DataLoader(trainset, batch_size=32, collate_fn=collate_func, shuffle=True) ...