Text Classification
Transformers
Safetensors
Hindi
English
xlm-roberta
multi-label-classification
toxicity
content-moderation
hinglish
code-mixed
indic-nlp
text-embeddings-inference
Instructions to use darelphilip/hinglish-toxicity-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use darelphilip/hinglish-toxicity-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="darelphilip/hinglish-toxicity-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("darelphilip/hinglish-toxicity-classifier") model = AutoModelForSequenceClassification.from_pretrained("darelphilip/hinglish-toxicity-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,308 Bytes
c23e77b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | {
"add_cross_attention": false,
"architectures": [
"XLMRobertaForSequenceClassification"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": 0,
"classifier_dropout": null,
"dtype": "float32",
"eos_token_id": 2,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
"0": "profanity_vulgarity",
"1": "targeted_abuse_harassment",
"2": "discriminatory_hate_speech",
"3": "caste",
"4": "communal_religious",
"5": "regional_xenophobic",
"6": "misogyny_gender"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"is_decoder": false,
"label2id": {
"caste": 3,
"communal_religious": 4,
"discriminatory_hate_speech": 2,
"misogyny_gender": 6,
"profanity_vulgarity": 0,
"regional_xenophobic": 5,
"targeted_abuse_harassment": 1
},
"layer_norm_eps": 1e-05,
"max_position_embeddings": 514,
"model_type": "xlm-roberta",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"output_past": true,
"pad_token_id": 1,
"position_embedding_type": "absolute",
"problem_type": "multi_label_classification",
"tie_word_embeddings": true,
"transformers_version": "5.15.0",
"type_vocab_size": 1,
"use_cache": false,
"vocab_size": 250002
}
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