Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use KingTechnician/roberta-base_Climate_Native with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KingTechnician/roberta-base_Climate_Native with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KingTechnician/roberta-base_Climate_Native")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KingTechnician/roberta-base_Climate_Native") model = AutoModelForSequenceClassification.from_pretrained("KingTechnician/roberta-base_Climate_Native") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "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": "ad hominem", | |
| "1": "ad populum", | |
| "2": "appeal to emotion", | |
| "3": "circular reasoning", | |
| "4": "equivocation", | |
| "5": "fallacy of credibility", | |
| "6": "fallacy of extension", | |
| "7": "fallacy of logic", | |
| "8": "fallacy of relevance", | |
| "9": "false causality", | |
| "10": "false dilemma", | |
| "11": "faulty generalization", | |
| "12": "intentional" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "ad hominem": 0, | |
| "ad populum": 1, | |
| "appeal to emotion": 2, | |
| "circular reasoning": 3, | |
| "equivocation": 4, | |
| "fallacy of credibility": 5, | |
| "fallacy of extension": 6, | |
| "fallacy of logic": 7, | |
| "fallacy of relevance": 8, | |
| "false causality": 9, | |
| "false dilemma": 10, | |
| "faulty generalization": 11, | |
| "intentional": 12 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.0.0", | |
| "type_vocab_size": 1, | |
| "use_cache": false, | |
| "vocab_size": 50265 | |
| } | |