Text Classification
Transformers
Safetensors
English
deberta-v2
deberta-v3
human value detection
schwartz values
moral values
political text
retrieval augmented classification
rag
multi-label classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use VictorYeste/value-context-rag-deberta-v3-base-doc-rag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VictorYeste/value-context-rag-deberta-v3-base-doc-rag with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VictorYeste/value-context-rag-deberta-v3-base-doc-rag")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VictorYeste/value-context-rag-deberta-v3-base-doc-rag") model = AutoModelForSequenceClassification.from_pretrained("VictorYeste/value-context-rag-deberta-v3-base-doc-rag") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "DebertaV2ForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "Self-direction: thought", | |
| "1": "Self-direction: action", | |
| "2": "Stimulation", | |
| "3": "Hedonism", | |
| "4": "Achievement", | |
| "5": "Power: dominance", | |
| "6": "Power: resources", | |
| "7": "Face", | |
| "8": "Security: personal", | |
| "9": "Security: societal", | |
| "10": "Tradition", | |
| "11": "Conformity: rules", | |
| "12": "Conformity: interpersonal", | |
| "13": "Humility", | |
| "14": "Benevolence: caring", | |
| "15": "Benevolence: dependability", | |
| "16": "Universalism: concern", | |
| "17": "Universalism: nature", | |
| "18": "Universalism: tolerance" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "Achievement": 4, | |
| "Benevolence: caring": 14, | |
| "Benevolence: dependability": 15, | |
| "Conformity: interpersonal": 12, | |
| "Conformity: rules": 11, | |
| "Face": 7, | |
| "Hedonism": 3, | |
| "Humility": 13, | |
| "Power: dominance": 5, | |
| "Power: resources": 6, | |
| "Security: personal": 8, | |
| "Security: societal": 9, | |
| "Self-direction: action": 1, | |
| "Self-direction: thought": 0, | |
| "Stimulation": 2, | |
| "Tradition": 10, | |
| "Universalism: concern": 16, | |
| "Universalism: nature": 17, | |
| "Universalism: tolerance": 18 | |
| }, | |
| "layer_norm_eps": 1e-07, | |
| "legacy": true, | |
| "max_position_embeddings": 512, | |
| "max_relative_positions": -1, | |
| "model_type": "deberta-v2", | |
| "norm_rel_ebd": "layer_norm", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "pooler_dropout": 0, | |
| "pooler_hidden_act": "gelu", | |
| "pooler_hidden_size": 768, | |
| "pos_att_type": [ | |
| "p2c", | |
| "c2p" | |
| ], | |
| "position_biased_input": false, | |
| "position_buckets": 256, | |
| "problem_type": "multi_label_classification", | |
| "relative_attention": true, | |
| "share_att_key": true, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.2.0", | |
| "type_vocab_size": 0, | |
| "vocab_size": 128100 | |
| } | |