Text Classification
Transformers
PyTorch
multilingual
bert
multilabel-classification
twitter
violence-prediction
text-embeddings-inference
Instructions to use m2im/smallLabse_finetuned_twitter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m2im/smallLabse_finetuned_twitter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="m2im/smallLabse_finetuned_twitter")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("m2im/smallLabse_finetuned_twitter") model = AutoModelForSequenceClassification.from_pretrained("m2im/smallLabse_finetuned_twitter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from m2im/smallLabse_finetuned_twitter: direct link, hf CLI and curl.
- Browser
- Download file 4.31 MB
-
https://huggingface.co/m2im/smallLabse_finetuned_twitter/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://m2im/smallLabse_finetuned_twitter@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/m2im/smallLabse_finetuned_twitter/resolve/refs%2Fpr%2F1/tokenizer.json
4.31 MB
File too large to display, you can check the raw version instead.