Text Classification
Transformers
ONNX
Safetensors
Transformers.js
modernbert
topic-classification
domain-classification
web-classification
weborganizer
data-curation
pretraining-data
mmbert
text-embeddings-inference
Instructions to use Horizon-Labs/multilingual-web-topic-format-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Horizon-Labs/multilingual-web-topic-format-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Horizon-Labs/multilingual-web-topic-format-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Horizon-Labs/multilingual-web-topic-format-base") model = AutoModelForSequenceClassification.from_pretrained("Horizon-Labs/multilingual-web-topic-format-base", device_map="auto") - Transformers.js
How to use Horizon-Labs/multilingual-web-topic-format-base with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'Horizon-Labs/multilingual-web-topic-format-base'); - Notebooks
- Google Colab
- Kaggle
Download config.json from Horizon-Labs/multilingual-web-topic-format-base: direct link, hf CLI and curl.
- Browser
- Download file 5.26 kB
-
https://huggingface.co/Horizon-Labs/multilingual-web-topic-format-base/resolve/main/config.json
- Command line
-
hf download hf://Horizon-Labs/multilingual-web-topic-format-base/config.json
-
curl -L -o config.json https://huggingface.co/Horizon-Labs/multilingual-web-topic-format-base/resolve/main/config.json
5.26 kB
| { | |
| "architectures": [ | |
| "ModernBertForSequenceClassification" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 2, | |
| "classifier_activation": "gelu", | |
| "classifier_bias": false, | |
| "classifier_dropout": 0.0, | |
| "classifier_pooling": "mean", | |
| "cls_token_id": 1, | |
| "decoder_bias": true, | |
| "deterministic_flash_attn": false, | |
| "dtype": "float32", | |
| "embedding_dropout": 0.0, | |
| "eos_token_id": 1, | |
| "global_attn_every_n_layers": 3, | |
| "gradient_checkpointing": false, | |
| "hidden_activation": "gelu", | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "topic_adult_content", | |
| "1": "topic_art_design", | |
| "2": "topic_software_development", | |
| "3": "topic_crime_law", | |
| "4": "topic_education_jobs", | |
| "5": "topic_electronics_hardware", | |
| "6": "topic_entertainment", | |
| "7": "topic_social_life", | |
| "8": "topic_fashion_beauty", | |
| "9": "topic_finance_business", | |
| "10": "topic_food_dining", | |
| "11": "topic_games", | |
| "12": "topic_health", | |
| "13": "topic_history_geography", | |
| "14": "topic_home_hobbies", | |
| "15": "topic_industrial", | |
| "16": "topic_literature", | |
| "17": "topic_politics", | |
| "18": "topic_religion", | |
| "19": "topic_science_math_technology", | |
| "20": "topic_software", | |
| "21": "topic_sports_fitness", | |
| "22": "topic_transportation", | |
| "23": "topic_travel_tourism", | |
| "24": "format_academic_writing", | |
| "25": "format_content_listing", | |
| "26": "format_creative_writing", | |
| "27": "format_customer_support_page", | |
| "28": "format_discussion_forum_comment_section", | |
| "29": "format_faqs", | |
| "30": "format_incomplete_content", | |
| "31": "format_knowledge_article", | |
| "32": "format_legal_notices", | |
| "33": "format_listicle", | |
| "34": "format_news_article", | |
| "35": "format_nonfiction_writing", | |
| "36": "format_organizational_about_page", | |
| "37": "format_organizational_announcement", | |
| "38": "format_personal_about_page", | |
| "39": "format_personal_blog", | |
| "40": "format_product_page", | |
| "41": "format_q_a_forum", | |
| "42": "format_spam_ads", | |
| "43": "format_structured_data", | |
| "44": "format_technical_writing", | |
| "45": "format_transcript_interview", | |
| "46": "format_tutorial_how_to_guide", | |
| "47": "format_user_reviews" | |
| }, | |
| "initializer_cutoff_factor": 2.0, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1152, | |
| "label2id": { | |
| "format_academic_writing": 24, | |
| "format_content_listing": 25, | |
| "format_creative_writing": 26, | |
| "format_customer_support_page": 27, | |
| "format_discussion_forum_comment_section": 28, | |
| "format_faqs": 29, | |
| "format_incomplete_content": 30, | |
| "format_knowledge_article": 31, | |
| "format_legal_notices": 32, | |
| "format_listicle": 33, | |
| "format_news_article": 34, | |
| "format_nonfiction_writing": 35, | |
| "format_organizational_about_page": 36, | |
| "format_organizational_announcement": 37, | |
| "format_personal_about_page": 38, | |
| "format_personal_blog": 39, | |
| "format_product_page": 40, | |
| "format_q_a_forum": 41, | |
| "format_spam_ads": 42, | |
| "format_structured_data": 43, | |
| "format_technical_writing": 44, | |
| "format_transcript_interview": 45, | |
| "format_tutorial_how_to_guide": 46, | |
| "format_user_reviews": 47, | |
| "topic_adult_content": 0, | |
| "topic_art_design": 1, | |
| "topic_crime_law": 3, | |
| "topic_education_jobs": 4, | |
| "topic_electronics_hardware": 5, | |
| "topic_entertainment": 6, | |
| "topic_fashion_beauty": 8, | |
| "topic_finance_business": 9, | |
| "topic_food_dining": 10, | |
| "topic_games": 11, | |
| "topic_health": 12, | |
| "topic_history_geography": 13, | |
| "topic_home_hobbies": 14, | |
| "topic_industrial": 15, | |
| "topic_literature": 16, | |
| "topic_politics": 17, | |
| "topic_religion": 18, | |
| "topic_science_math_technology": 19, | |
| "topic_social_life": 7, | |
| "topic_software": 20, | |
| "topic_software_development": 2, | |
| "topic_sports_fitness": 21, | |
| "topic_transportation": 22, | |
| "topic_travel_tourism": 23 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "layer_types": [ | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention" | |
| ], | |
| "local_attention": 128, | |
| "mask_token_id": 4, | |
| "max_position_embeddings": 8192, | |
| "mlp_bias": false, | |
| "mlp_dropout": 0.0, | |
| "model_type": "modernbert", | |
| "norm_bias": false, | |
| "norm_eps": 1e-05, | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 22, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "sans_pos", | |
| "problem_type": "multi_label_classification", | |
| "rope_parameters": { | |
| "full_attention": { | |
| "rope_theta": 160000, | |
| "rope_type": "default" | |
| }, | |
| "sliding_attention": { | |
| "rope_theta": 160000, | |
| "rope_type": "default" | |
| } | |
| }, | |
| "sep_token_id": 1, | |
| "sparse_pred_ignore_index": -100, | |
| "sparse_prediction": false, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.17.0", | |
| "uses_context": false, | |
| "vocab_size": 256000 | |
| } | |