Text Classification
Transformers
Safetensors
English
roberta
sequence-classification
distilroberta
climate-change
logical-fallacy-detection
nlp
Eval Results (legacy)
text-embeddings-inference
Instructions to use SteadyHands/climate-fallacy-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SteadyHands/climate-fallacy-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SteadyHands/climate-fallacy-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SteadyHands/climate-fallacy-roberta") model = AutoModelForSequenceClassification.from_pretrained("SteadyHands/climate-fallacy-roberta") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "RobertaForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "CHERRY_PICKING", | |
| "1": "EVADING_THE_BURDEN_OF_PROOF", | |
| "2": "FALSE_ANALOGY", | |
| "3": "FALSE_AUTHORITY", | |
| "4": "FALSE_CAUSE", | |
| "5": "HASTY_GENERALISATION", | |
| "6": "NO_FALLACY", | |
| "7": "POST_HOC", | |
| "8": "RED_HERRINGS", | |
| "9": "STRAWMAN", | |
| "10": "VAGUENESS" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "CHERRY_PICKING": 0, | |
| "EVADING_THE_BURDEN_OF_PROOF": 1, | |
| "FALSE_ANALOGY": 2, | |
| "FALSE_AUTHORITY": 3, | |
| "FALSE_CAUSE": 4, | |
| "HASTY_GENERALISATION": 5, | |
| "NO_FALLACY": 6, | |
| "POST_HOC": 7, | |
| "RED_HERRINGS": 8, | |
| "STRAWMAN": 9, | |
| "VAGUENESS": 10 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 6, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "single_label_classification", | |
| "transformers_version": "4.57.3", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 50265 | |
| } | |