Instructions to use EthioNLP/EthioLLM-b-250K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EthioNLP/EthioLLM-b-250K with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EthioNLP/EthioLLM-b-250K")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EthioNLP/EthioLLM-b-250K") model = AutoModelForMaskedLM.from_pretrained("EthioNLP/EthioLLM-b-250K") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c1f0ae3266e78655f6fd4a41efbd81c6006fcc17d86ff651bcce9d8fd19484f
- Size of remote file:
- 1.11 GB
- SHA256:
- eb793d01c52336bf5efbac945dcf80c5c68a52b191a209020a041aea966e8b5b
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