Instructions to use UBC-NLP/serengeti-E110 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/serengeti-E110 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="UBC-NLP/serengeti-E110")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/serengeti-E110") model = AutoModel.from_pretrained("UBC-NLP/serengeti-E110", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +0 -1
config.json
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{
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"_name_or_path": "/home/elmadany/projects/rrg-mageed/DataBank/African_data/African_languages_datasets/African_LM/LM_models/model_110K_vocab/models/electra_africa110_base/pytorch/discriminator-110K-base-3365666@3.4M/",
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"architectures": [
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"ElectraModel"
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],
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{
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"architectures": [
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"ElectraModel"
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],
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