Text Classification
Transformers
ONNX
Safetensors
Transformers.js
modernbert
sentiment-analysis
sentiment
mmbert
text-embeddings-inference
Instructions to use Horizon-Labs/multilingual-sentiment-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Horizon-Labs/multilingual-sentiment-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Horizon-Labs/multilingual-sentiment-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Horizon-Labs/multilingual-sentiment-small") model = AutoModelForSequenceClassification.from_pretrained("Horizon-Labs/multilingual-sentiment-small", device_map="auto") - Transformers.js
How to use Horizon-Labs/multilingual-sentiment-small with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'Horizon-Labs/multilingual-sentiment-small'); - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Horizon-Labs/multilingual-sentiment-small: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/Horizon-Labs/multilingual-sentiment-small/resolve/main/tokenizer.json
- Command line
-
hf download hf://Horizon-Labs/multilingual-sentiment-small/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Horizon-Labs/multilingual-sentiment-small/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 4979ea4051b704efcb2a1a34961c5f93d2fa004f33c607d894c7ebe32511f588
- Size of remote file:
- 34.4 MB
- SHA256:
- f34b44a6dc8a0eef651bfa10e8325057530152606a69d9c3b6ae02efb1558f0a
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