Text Classification
Transformers
ONNX
Safetensors
Transformers.js
modernbert
prompt-classification
task-classification
prompt-complexity
llm-routing
model-routing
data-curation
mmbert
text-embeddings-inference
Instructions to use Horizon-Labs/multilingual-prompt-task-complexity-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Horizon-Labs/multilingual-prompt-task-complexity-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Horizon-Labs/multilingual-prompt-task-complexity-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Horizon-Labs/multilingual-prompt-task-complexity-base") model = AutoModelForSequenceClassification.from_pretrained("Horizon-Labs/multilingual-prompt-task-complexity-base", device_map="auto") - Transformers.js
How to use Horizon-Labs/multilingual-prompt-task-complexity-base with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'Horizon-Labs/multilingual-prompt-task-complexity-base'); - Notebooks
- Google Colab
- Kaggle
Download config.json from Horizon-Labs/multilingual-prompt-task-complexity-base: direct link, hf CLI and curl.
- Browser
- Download file 2.95 kB
-
https://huggingface.co/Horizon-Labs/multilingual-prompt-task-complexity-base/resolve/main/config.json
- Command line
-
hf download hf://Horizon-Labs/multilingual-prompt-task-complexity-base/config.json
-
curl -L -o config.json https://huggingface.co/Horizon-Labs/multilingual-prompt-task-complexity-base/resolve/main/config.json
2.95 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": "task_open_qa", | |
| "1": "task_closed_qa", | |
| "2": "task_summarization", | |
| "3": "task_text_generation", | |
| "4": "task_code_generation", | |
| "5": "task_chatbot", | |
| "6": "task_classification", | |
| "7": "task_rewrite", | |
| "8": "task_brainstorming", | |
| "9": "task_extraction", | |
| "10": "task_other", | |
| "11": "creativity", | |
| "12": "reasoning", | |
| "13": "contextual_knowledge", | |
| "14": "domain_knowledge", | |
| "15": "constraints", | |
| "16": "complexity" | |
| }, | |
| "initializer_cutoff_factor": 2.0, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1152, | |
| "label2id": { | |
| "complexity": 16, | |
| "constraints": 15, | |
| "contextual_knowledge": 13, | |
| "creativity": 11, | |
| "domain_knowledge": 14, | |
| "reasoning": 12, | |
| "task_brainstorming": 8, | |
| "task_chatbot": 5, | |
| "task_classification": 6, | |
| "task_closed_qa": 1, | |
| "task_code_generation": 4, | |
| "task_extraction": 9, | |
| "task_open_qa": 0, | |
| "task_other": 10, | |
| "task_rewrite": 7, | |
| "task_summarization": 2, | |
| "task_text_generation": 3 | |
| }, | |
| "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 | |
| } | |