Instructions to use Hartunka/tiny_bert_rand_100_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hartunka/tiny_bert_rand_100_v1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, DistilBertForLDAMaskedLM tokenizer = AutoTokenizer.from_pretrained("Hartunka/tiny_bert_rand_100_v1") model = DistilBertForLDAMaskedLM.from_pretrained("Hartunka/tiny_bert_rand_100_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 266 Bytes
befbef8 | 1 2 3 4 5 6 7 8 9 10 | {
"epoch": 25.0,
"eval_accuracy": 0.15251172515115557,
"eval_loss": 10.893685340881348,
"eval_runtime": 0.7516,
"eval_samples": 479,
"eval_samples_per_second": 637.341,
"eval_steps_per_second": 6.653,
"perplexity": 53835.33639612944
} |