Instructions to use g8a9/roberta-tiny-10M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use g8a9/roberta-tiny-10M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="g8a9/roberta-tiny-10M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("g8a9/roberta-tiny-10M") model = AutoModelForMaskedLM.from_pretrained("g8a9/roberta-tiny-10M") - Notebooks
- Google Colab
- Kaggle
File size: 443 Bytes
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"epoch": 89.58,
"eval_accuracy": 0.5148013040185571,
"eval_loss": 2.73911714553833,
"eval_runtime": 145.896,
"eval_samples": 24055,
"eval_samples_per_second": 164.878,
"eval_steps_per_second": 5.154,
"perplexity": 15.47331837619993,
"train_loss": 3.7431876293448516,
"train_runtime": 42244.2763,
"train_samples": 24910,
"train_samples_per_second": 58.967,
"train_steps_per_second": 0.114
} |