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nlpre_trankit_ud_xlm-roberta-large_nkjp-by-name
ipipan/nlpre_trankit_ud_xlm-roberta-large_nkjp-by-name
nlpre_trankit_ud_xlm-roberta-large_nkjp-by-name is a machine learning model from ipipan. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
- Morphosyntactic analyzer: Trankit - Tagset: UD - Embedding vectors: XLM-RoBERTa-Large - Dataset: NLPrePL-NKJP-fair-by-name (https://huggingface.co/datasets/ipipan/nlprepl)
Access
Public
Updated Oct 3, 2023
Repo size
148 MB
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.mdl132 MB · 75%
At a glance
- Access
- Public
- Created
- Sep 28, 2023
- Updated
- Oct 3, 2023
- SHA
- 1285fcd4
Spaces
Model card
From the Hugging Face model README
Model description
- Morphosyntactic analyzer: Trankit
- Tagset: UD
- Embedding vectors: XLM-RoBERTa-Large
- Dataset: NLPrePL-NKJP-fair-by-name (https://huggingface.co/datasets/ipipan/nlprepl)
How to use
Clone
git clone [email protected]:ipipan/nlpre_trankit_ud_xlm-roberta-large_nkjp-by-name
Load model
import trankit
model_path = './nlpre_trankit_ud_xlm-roberta-large_nkjp-by-name'
trankit.verify_customized_pipeline(
category='customized-mwt', # pipeline category
save_dir=model_path, # directory used for saving models in previous steps
embedding_name='xlm-roberta-large' # embedding version that we use for training our customized pipeline, by default, it is `xlm-roberta-base`
)
model = trankit.Pipeline(lang='customized-mwt', cache_dir=model_path, embedding='xlm-roberta-large')
- Created
- Sep 28, 2023
- Updated
- Oct 3, 2023