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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4eb19d75363fe071fc6940432ae6b21a7a61ecabd908b3fadf4752e32783a77c
- Size of remote file:
- 5.3 kB
- SHA256:
- b236c0038dc96b91289a01508680db4e0ce9cf8a2b9257d44a70f1b20f8f6580
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.