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        "description": "## Installation instructions\n\n1. Download and install the latest Anaconda distribution from [here](https://www.anaconda.com/distribution/#download-section)\n\n2. Start the *Anaconda Powershell Prompt* if running Windows, or a terminal otherwise. Make sure conda is available in the command line path.\n\n3. Create a conda environment running `conda create -n pvcastro-iberlef python=3.6`\n\n4. Update Anaconda running `conda update -n base -c defaults conda`\n\n5. Install pytorch running `conda install pytorch-cpu -c pytorch -n pvcastro-iberlef`\n\n6. Activate the created conda environment using `conda activate pvcastro-iberlef`\n\n7. Install the AllenNLP framework running `pip install -U allennlp`\n\n8. Download the spacy model running `python -m spacy download en_core_web_sm`\n\n9. Install the pvcastro-iberlef module running `pip install -U pvcastro-iberlef`\n\n---\n\n## Execution instructions\n\nRun the NER prediction with a command as `python -m pvcastro_iberlef.predict_ner --document-path path_to_the_input_document --out-path path_to_the_output_file`\n\nParameters: \n\n- **document-path**: path to the document containing the text to be predicted for NER, with one token per line, with sentences separated by blank lines.\n- **out-path**: path to the document where the predictions results will be written. **Must specify a filename**. Example: C:\\iberlef\\predictions.txt\n\n## Observations\n\nSince the IberLEF NER model uses two language models based on [ELMo](https://github.com/allenai/allennlp/blob/master/tutorials/how_to/elmo.md), the trained model ended up quite big, with **1.4Gb aproximately**. It takes a while to download it the first time, but the model is cached, so following executions after the first will be quicker. \n\n\n",
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