Text Classification
Transformers
Safetensors
modernbert
mmbert
sentiment-analysis
twitter
multilingual
text-embeddings-inference
Instructions to use Ido-shraga/mmbert-base-sentiment-adapted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ido-shraga/mmbert-base-sentiment-adapted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ido-shraga/mmbert-base-sentiment-adapted")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ido-shraga/mmbert-base-sentiment-adapted") model = AutoModelForSequenceClassification.from_pretrained("Ido-shraga/mmbert-base-sentiment-adapted", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Ido-shraga/mmbert-base-sentiment-adapted: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/Ido-shraga/mmbert-base-sentiment-adapted/resolve/main/tokenizer.json
- Command line
-
hf download hf://Ido-shraga/mmbert-base-sentiment-adapted/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Ido-shraga/mmbert-base-sentiment-adapted/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- cc6fc0c630b76bc4a78de4965bd7ce0381446e80a84f40aad512a75e6a43d849
- Size of remote file:
- 34.4 MB
- SHA256:
- b7cc6d8599efc7f57ee2fe874a7e29b82038c5dfd03a442652c2afea13fe41e5
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