Instructions to use EthioNLP/EthioLLM-b-70k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EthioNLP/EthioLLM-b-70k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EthioNLP/EthioLLM-b-70k")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EthioNLP/EthioLLM-b-70k") model = AutoModelForMaskedLM.from_pretrained("EthioNLP/EthioLLM-b-70k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from EthioNLP/EthioLLM-b-70k: direct link, hf CLI and curl.
- Browser
- Download file 560 MB
-
https://huggingface.co/EthioNLP/EthioLLM-b-70k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://EthioNLP/EthioLLM-b-70k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/EthioNLP/EthioLLM-b-70k/resolve/main/pytorch_model.bin
560 MB
- Xet hash:
- 3768dce0f61a743372c306055978b8e7695341755830928c3044678b7db59784
- Size of remote file:
- 560 MB
- SHA256:
- 77084c3681ca7e8c3ca12fe1023eca75344c2806ad9bf61bccfb948a1986e635
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