<jupyter_start><jupyter_text>load classifieroptions* knn_filter<jupyter_code>genome_cls = get_classifier('knn_filter')<jupyter_output><empty_output><jupyter_text>load templateoptions* template_core* template_gram_neg* template_gram_pos<jupyter_code>core_template = get_template('template_core')
core_template['id']
from modelseedpy.core.mstemplate import MSTemplateBuilder
template = MSTemplateBuilder.from_dict(core_template).build()
template
template_reaction = template.reactions[0]
template_reaction
template_reaction.to_reaction()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.0920353982300885, 'fraction_numerical': 0.0017699115044247787, 'mean_word_length': 17.258064516129032, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '537429', 'license': 'MIT', 'n_tokens_mistral': 191, 'n_tokens_neox': 185, 'n_words': 21, 'path': 'examples/Others/download_templates.ipynb', 'repo_name': 'Fxe/ModelSEEDpy', 'size': '565'}