Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use achDev/medidalRoberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use achDev/medidalRoberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="achDev/medidalRoberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("achDev/medidalRoberta") model = AutoModelForSequenceClassification.from_pretrained("achDev/medidalRoberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5c8060b7c04a37cf4a9603a0506da7181a8b41a8bbbc37b129433f6e25716fa
- Size of remote file:
- 4.92 kB
- SHA256:
- 0c7150529842f4f2a3b48990488eebc34c3dfbd0201d2f57bcee99f14000b662
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.