Instructions to use Hartunka/bert_base_rand_20_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hartunka/bert_base_rand_20_v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, DistilBertForLDAMaskedLM tokenizer = AutoTokenizer.from_pretrained("Hartunka/bert_base_rand_20_v2") model = DistilBertForLDAMaskedLM.from_pretrained("Hartunka/bert_base_rand_20_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 264 Bytes
164a1a9 | 1 2 3 4 5 6 7 8 9 10 | {
"epoch": 25.0,
"eval_accuracy": 0.15350059332090185,
"eval_loss": 9.08564567565918,
"eval_runtime": 1.0357,
"eval_samples": 479,
"eval_samples_per_second": 462.482,
"eval_steps_per_second": 4.828,
"perplexity": 8827.663732722915
} |