Comments (4)
Hey @peteriz , I'd like to help with this. As someone who would be coming into this project completely new, any basics I should get familiar with or hurdles you can foresee?
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Hi @Wittionary, the idea is to create a simple dockerfile that contains python 3.6 and nlp-architect installed properly (cpu or gpu).
In addition, expose a port with the demo running (see nlp_architect server
command that launches a small UI with our 4 pre-trained models) so that it could be fired-up easily with Docker.
Thanks!
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@peteriz Why was this closed? Could you include an explanation?
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@jacobkdick we've added a Dockerfile with the release last week.
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Related Issues (20)
- question: How can i use the Topic and Trend Analysis Solution HOT 1
- How to improve bist model accuracy? :Bistmodel HOT 6
- Terms file is empty, no terms to re-rank HOT 1
- dimension error HOT 1
- url for quant BERT config.json is invalid HOT 1
- bug: [an error occurred while running Q8BERT] HOT 3
- bug: [In ABSA Opinion lixicon and Aspect lexicon are not being written to a csv when you run train.py] HOT 4
- bug: ABSA: Passing spacy_model="fr_core_news_sm" to SentimentInference gives an error HOT 2
- question: [Evaluation results of the Q8BERT] HOT 2
- Problem with installing nlp-architect in google-colab HOT 2
- bug: [Memory error while training the absa solution model] HOT 3
- bug: Couldn't reach server for bert-base-uncased model URL HOT 1
- bug: zipfile.BadZipFile using pretrained BIST model HOT 4
- improvement: distillation for TransformerSequenceClassifier models for GLUE tasks
- question: [Q8Bert experiment Setting] HOT 2
- question: [Quantization] Which files to change to make inference faster for Q8BERT? HOT 1
- bug: ERROR: ResolutionImpossible
- Why the number of data from restaurant and laptop is different from the paper?
- question: [question topic]
- Performance issue in the definition of _inference, examples/memn2n_dialogue/memn2n_dialogue.py(P1) HOT 2
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