Instructions to use novelcore/gem-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use novelcore/gem-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="novelcore/gem-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("novelcore/gem-roberta") model = AutoModelForMaskedLM.from_pretrained("novelcore/gem-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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### Pre-training
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The model was pre-trained from scratch for **150,000 steps** on 8x NVIDIA A100 40GB GPUs, using BFloat16 (`bf16`) mixed-precision for stability and speed. The training took approximately **
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The key hyperparameters used were:
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### Pre-training
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The model was pre-trained from scratch for **150,000 steps** on 8x NVIDIA A100 40GB GPUs, using BFloat16 (`bf16`) mixed-precision for stability and speed. The training took approximately **81 hours and 39 minutes** to complete.
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The key hyperparameters used were:
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