Text Classification
Transformers
ONNX
Safetensors
Transformers.js
modernbert
question-detection
query-classification
haystack
rag
search
mmbert
text-embeddings-inference
Instructions to use Horizon-Labs/multilingual-question-vs-statement-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Horizon-Labs/multilingual-question-vs-statement-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Horizon-Labs/multilingual-question-vs-statement-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Horizon-Labs/multilingual-question-vs-statement-small") model = AutoModelForSequenceClassification.from_pretrained("Horizon-Labs/multilingual-question-vs-statement-small", device_map="auto") - Transformers.js
How to use Horizon-Labs/multilingual-question-vs-statement-small with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'Horizon-Labs/multilingual-question-vs-statement-small'); - Notebooks
- Google Colab
- Kaggle
Download training/data_stats.json from Horizon-Labs/multilingual-question-vs-statement-small: direct link, hf CLI and curl.
- Browser
- Download file 228 Bytes
-
https://huggingface.co/Horizon-Labs/multilingual-question-vs-statement-small/resolve/main/training/data_stats.json
- Command line
-
hf download hf://Horizon-Labs/multilingual-question-vs-statement-small/training/data_stats.json
-
curl -L -o data_stats.json https://huggingface.co/Horizon-Labs/multilingual-question-vs-statement-small/resolve/main/training/data_stats.json
228 Bytes
| { | |
| "train": 391465, | |
| "val": 20610, | |
| "by_source": { | |
| "sentence": 299322, | |
| "query": 112753 | |
| }, | |
| "n_lang": 67, | |
| "pos_rate": 0.399, | |
| "test_sentences": 11357, | |
| "test_sent_langs": 66, | |
| "test_queries": 9399, | |
| "test_query_langs": 47 | |
| } |