Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use albertmartinez/openalex-topic-classification-title-abstract with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albertmartinez/openalex-topic-classification-title-abstract with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="albertmartinez/openalex-topic-classification-title-abstract")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("albertmartinez/openalex-topic-classification-title-abstract") model = AutoModelForSequenceClassification.from_pretrained("albertmartinez/openalex-topic-classification-title-abstract") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 10.0, | |
| "total_flos": 9.242888597926871e+18, | |
| "train_loss": 2.4459246747957275, | |
| "train_runtime": 102710.4528, | |
| "train_samples": 3376092, | |
| "train_samples_per_second": 328.7, | |
| "train_steps_per_second": 2.568 | |
| } |