Instructions to use uhhlt/am-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uhhlt/am-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="uhhlt/am-roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("uhhlt/am-roberta") model = AutoModelForMaskedLM.from_pretrained("uhhlt/am-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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---
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language:
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- am
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thumbnail: "https://raw.githubusercontent.com/uhh-lt/amharicmodels/master/logo.png?token=AAIB2MYMI6TSIK7CHWYGHKTBQ3FQS"
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tags:
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- Amharic
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- Semetic language
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license: "mit"
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datasets:
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- Amharic corpus from LT group, UHH
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---
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## This is the Amharic RoBERTa transformer-based LM
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