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CJIS v3.0 cjis-sentiments-classifier - Climate journalism multi-label classifier

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  1. README.md +40 -0
  2. config.json +50 -0
  3. model.safetensors +3 -0
  4. tokenizer.json +0 -0
  5. tokenizer_config.json +21 -0
README.md ADDED
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+ ---
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+ language: en
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+ license: mit
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+ library_name: pytorch
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+ tags:
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+ - climate-journalism
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+ - cjis-copilot
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+ - sentiments
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+ - multi-label-classification
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+ # Base: Custom MLM-trained DeBERTa (not on HuggingFace Hub)
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+ ---
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+
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+ # CJIS Co-pilot: Sentiments Classifier
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+
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+ Part of the Climate Journalism Intelligence System (CJIS) v3.0 "Journalistic Co-pilot".
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+
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+ ## Architecture
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+ - Base: Climate-pretrained DeBERTa (MLM on 20k climate articles)
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+ - Head: Specialist classifier for sentiments
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+
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+ ## Task
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+ Sentiments classification for climate journalism articles.
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+
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+ ## Labels (4)
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+ - `alarm_urgent`
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+ - `critical_skeptical`
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+ - `solution_oriented`
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+ - `neutral_balanced`
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+
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+ ## Usage
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+ ```python
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+ from transformers import pipeline
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+
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+ classifier = pipeline(
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+ "text-classification",
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+ model="maai-org/cjis-sentiments-classifier",
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+ return_all_scores=True
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+ )
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+
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+ result = classifier("Your climate article here...")
config.json ADDED
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+ {
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+ "DebertaV2ForSequenceClassification"
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "alarm_urgent",
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+ "1": "critical_skeptical",
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+ "2": "solution_oriented",
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+ "3": "neutral_balanced"
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+ },
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+ "label2id": {
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+ "alarm_urgent": 0,
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+ "critical_skeptical": 1,
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+ "neutral_balanced": 3,
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+ "solution_oriented": 2
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+ },
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+ "layer_norm_eps": 1e-07,
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+ "legacy": true,
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+ "max_position_embeddings": 512,
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+ "max_relative_positions": -1,
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+ "model_type": "deberta-v2",
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+ "norm_rel_ebd": "layer_norm",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pooler_hidden_act": "gelu",
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+ "pooler_hidden_size": 768,
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+ "pos_att_type": [
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+ "p2c",
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+ "c2p"
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+ "position_biased_input": false,
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+ "position_buckets": 256,
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+ "relative_attention": true,
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+ "transformers_version": "5.0.0",
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+ "vocab_size": 128100
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+ }
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tokenizer.json ADDED
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