Text Classification
Transformers
TensorBoard
Safetensors
modernbert
sentiment
multilingual
sentiment-analysis
product-reviews
place-reviews
text-embeddings-inference
Instructions to use clapAI/modernBERT-large-multilingual-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clapAI/modernBERT-large-multilingual-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clapAI/modernBERT-large-multilingual-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clapAI/modernBERT-large-multilingual-sentiment") model = AutoModelForSequenceClassification.from_pretrained("clapAI/modernBERT-large-multilingual-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from clapAI/modernBERT-large-multilingual-sentiment: direct link, hf CLI and curl.
- Browser
- Download file 6.9 kB
-
https://huggingface.co/clapAI/modernBERT-large-multilingual-sentiment/resolve/main/training_args.bin
- Command line
-
hf download hf://clapAI/modernBERT-large-multilingual-sentiment/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/clapAI/modernBERT-large-multilingual-sentiment/resolve/main/training_args.bin
6.9 kB
- Xet hash:
- bad62610ffa830059cfa3bfedfea74b10b3d06a96a8ce3b3df920619319c014b
- Size of remote file:
- 6.9 kB
- SHA256:
- 8c56357ef933ecc57ec418134405509dfabe98cd69066832a6493bf910934fe5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.