Comments (3)
Thanks for asking, we do provide such kind of scripts. Pls check ReadMe
BTW, GPUs are highly recommended for training and inference. We found that GPUs can bring not only better efficiency but also better effectiveness (in some cases).
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Also, i'd like to mention that we provide some pre-trained models at ReadMe
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I loss my focus on ReadMe , sorry for brother about this naive question !
And thanks for kind tips about use GPU . I will try it later.
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Related Issues (20)
- train_w.py Error HOT 2
- Mismatch of performance between this repository and the paper HOT 6
- How can I include handcrafted features in NER ?
- evaluator.calc_score HOT 3
- where is the dictory './data'
- AttributeError: module 'torch._C' has no attribute '_cuda_setDevice' HOT 3
- KeyError in predictor.py class predict HOT 1
- Question about POS performance HOT 2
- How to deal with sentences with different lengths?
- train_w.py Error, TypeError: can't convert np.ndarray of type numpy.object_ HOT 2
- Is word level bi-lstm reflected in the code ? HOT 1
- About the score given a sequence and a target
- anyone can update to pytorch1.0
- Missing "eval_batch" in train_w.py line 163 HOT 1
- RuntimeError: HOT 1
- dropout
- RuntimeError: expand(torch.LongTensor{[50, 1]}, size=[50]): the number of sizes provided (1) must be greater or equal to the number of dimensions in the tensor (2)
- How do you tune the model to get a large # of keywords outputted by the CRF layer? HOT 1
- Incorrect Precision Output for test_rec HOT 1
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