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 tokenizer.json from Horizon-Labs/multilingual-question-vs-statement-small: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/Horizon-Labs/multilingual-question-vs-statement-small/resolve/main/tokenizer.json
- Command line
-
hf download hf://Horizon-Labs/multilingual-question-vs-statement-small/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Horizon-Labs/multilingual-question-vs-statement-small/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- cc6fc0c630b76bc4a78de4965bd7ce0381446e80a84f40aad512a75e6a43d849
- Size of remote file:
- 34.4 MB
- SHA256:
- b7cc6d8599efc7f57ee2fe874a7e29b82038c5dfd03a442652c2afea13fe41e5
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