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Runtime error
| # | |
| # | |
| # def make_predict(model_name_global, model_local, decode_dict, title, abstract): | |
| # model_name_global="allenai/scibert_scivocab_uncased" | |
| # model_local="scibert_trainer/checkpoint-2000/" | |
| # | |
| # tokenizer_ = AutoTokenizer.from_pretrained(model_name_global) | |
| # tokens = tokenizer_(title + abstract, return_tensors="pt") | |
| # model_ = AutoModelForSequenceClassification.from_pretrained(model_local) | |
| # outs = model_(tokens.input_ids) | |
| # | |
| # probs = outs["logits"].softmax(dim=-1).tolist()[0] | |
| # topic_probs = {} | |
| # for i, p in enumerate(probs): | |
| # if p > 0.1: | |
| # topic_probs[decode_dict[i]] = p | |
| # return topic_probs |