Text Classification
Transformers
ONNX
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use albertmartinez/bert-multilingual-sdg-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albertmartinez/bert-multilingual-sdg-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="albertmartinez/bert-multilingual-sdg-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("albertmartinez/bert-multilingual-sdg-classification") model = AutoModelForSequenceClassification.from_pretrained("albertmartinez/bert-multilingual-sdg-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "total_flos": 4.52871045169152e+16, | |
| "train_loss": 0.9877658092399512, | |
| "train_runtime": 691.6026, | |
| "train_samples": 34420, | |
| "train_samples_per_second": 248.842, | |
| "train_steps_per_second": 3.89 | |
| } |