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
File size: 994 Bytes
aa93893 | 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 | {
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"task_macro_f1": 0.3176954339403373,
"task_acc_lang_mean": 0.4588095238095239,
"task_acc_en": 0.655,
"spearman_creativity": 0.4777647258895101,
"spearman_reasoning": 0.2497500089936578,
"spearman_contextual_knowledge": 0.2302563300742145,
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"spearman_constraints": 0.6480432086980401,
"spearman_complexity": 0.3471741488551528,
"spearman_mean": 0.3896955872664494
},
"teacher": {
"n": 4200,
"task_acc": 0.8557142857142858,
"task_macro_f1": 0.8071549940704531,
"task_acc_lang_mean": 0.8557142857142856,
"task_acc_en": 0.915,
"spearman_creativity": 0.8556580154707426,
"spearman_reasoning": 0.8302711408392133,
"spearman_contextual_knowledge": 0.6876942315551514,
"spearman_domain_knowledge": 0.808322633505938,
"spearman_constraints": 0.9146826907015201,
"spearman_complexity": 0.8191655790270074,
"spearman_mean": 0.8192990485165955
}
} |