README.md

metadata

license: eupl-1.1
language:
  - el
library_name: fasttext
pipeline_tag: text-classification

ilsp/justice

repo_id = "ilsp/justice"
model_path = hf_hub_download(repo_id=repo_id, filename="20241124-model.ftz")
sample_decision = hf_hub_download(repo_id=repo_id, filename="sample_data/Α2485_2023.txt")
model = load_model(model_path)
labels_map =  {
  'preamble': '__label__0', '__label__0': 'preamble',
  'panel': '__label__1', '__label__1': 'panel',
  'litigants': '__label__2', '__label__2': 'litigants',
  'justification': '__label__3', '__label__3': 'justification',
  'decision': '__label__4', '__label__4': 'decision',
  'post': '__label__5', '__label__5': 'post'}

with open(sample_decision) as inf:
    paras = [p for p in inf.read().split(NL) if p.strip()]
    random.shuffle(paras)
    text = NL.join(paras)

nchars = 150
for line in text.split(NL):
    pred = labels_map[model.predict(line.strip())[0][0]]
    if len(line) > nchars:
        line = line[0:nchars]
    print(f"{line} -> {pred}")