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
File size: 240 Bytes
bbba21f | 1 2 3 4 5 6 7 8 9 | {
"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
} |