Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Merlinooooo/sentiment-analysis-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Merlinooooo/sentiment-analysis-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Merlinooooo/sentiment-analysis-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Merlinooooo/sentiment-analysis-test") model = AutoModelForSequenceClassification.from_pretrained("Merlinooooo/sentiment-analysis-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0768235da1d7ea1df7e8f25341577986e664fdb84e6d0f1f220e0c2cd230292d
- Size of remote file:
- 1.11 GB
- SHA256:
- d0766ba5efa8dd4f0171e4dc1890972ca79c4f2bbbe49e3848ccff6266ee7d23
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.