Instructions to use HiTZ/xlm-roberta-large-lemma-pl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/xlm-roberta-large-lemma-pl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HiTZ/xlm-roberta-large-lemma-pl")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HiTZ/xlm-roberta-large-lemma-pl") model = AutoModelForTokenClassification.from_pretrained("HiTZ/xlm-roberta-large-lemma-pl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HiTZ/xlm-roberta-large-lemma-pl: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/HiTZ/xlm-roberta-large-lemma-pl/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HiTZ/xlm-roberta-large-lemma-pl/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HiTZ/xlm-roberta-large-lemma-pl/resolve/main/pytorch_model.bin
2.24 GB
- Xet hash:
- 018dcd8719d2aad88343d7beb2f013997584c3bdcff264db2b4c764230e3b63d
- Size of remote file:
- 2.24 GB
- SHA256:
- f369b4cfdf72545d68dd84bdc1a5390959d1c40b4795e70f4752891c0da86a4d
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