Instructions to use Nehc/rst with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nehc/rst with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Nehc/rst", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Nehc/rst: direct link, hf CLI and curl.
- Browser
- Download file 685 Bytes
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https://huggingface.co/Nehc/rst/resolve/main/README.md
- Command line
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hf download hf://Nehc/rst/README.md
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curl -L -o README.md https://huggingface.co/Nehc/rst/resolve/main/README.md
685 Bytes
metadata
license: mit
language:
- ru
library_name: transformers
Annoy vector db of Russian Synodal Translation (RST) of Bible
Embdding by intfloat/multilingual-e5-large
Ussage:
rst_ind = AnnoyIndex(1024, metric='angular')
rst_ind.load('rst.indx')
rst_df = pandas.read_csv('rst_db.csv')
embd = GetE5Emb("Как жить правильно и не совершить греха?") # see the origin e5-large usage
indices = rst_ind.get_nns_by_vector(emb, 3)
ind = random.choice(indices)
str_ = rst_df.loc[ind].Text
print(f"{str_} [{rst_df.loc[ind]['Book']}{rst_df.loc[ind]['Chapter']}:{rst_df.loc[ind]['Verse']}]")