Instructions to use yarongef/DistilProtBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yarongef/DistilProtBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="yarongef/DistilProtBert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("yarongef/DistilProtBert") model = AutoModelForMaskedLM.from_pretrained("yarongef/DistilProtBert") - Notebooks
- Google Colab
- Kaggle
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README.md
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Differences between DistilProtBert model and ProtBert:
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| **Model** | **Parameters** | **Hidden layers** | **Pretraining sequences** | **Pretraining hardware** |
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|:--------------:|:--------------:|:-----------------:|:-------------------------:|:------------------------:|
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| ProtBert | 420M | 30 | 43M | 5 v100 32GB GPUs |
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| DistilProtBert | 230M | 15 | 216M | 512 16GB Tpus |
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Differences between DistilProtBert model and ProtBert:
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| **Model** | **# of Parameters** | **# of Hidden layers** | **# of Pretraining sequences** | **Pretraining hardware** |
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|:--------------:|:--------------:|:-----------------:|:-------------------------:|:------------------------:|
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| ProtBert | 420M | 30 | 43M | 5 v100 32GB GPUs |
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| DistilProtBert | 230M | 15 | 216M | 512 16GB Tpus |
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