Instructions to use ruanchaves/xlm-roberta-base-harem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruanchaves/xlm-roberta-base-harem with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ruanchaves/xlm-roberta-base-harem")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ruanchaves/xlm-roberta-base-harem") model = AutoModelForTokenClassification.from_pretrained("ruanchaves/xlm-roberta-base-harem", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ruanchaves/xlm-roberta-base-harem: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/ruanchaves/xlm-roberta-base-harem/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ruanchaves/xlm-roberta-base-harem/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ruanchaves/xlm-roberta-base-harem/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 8c1489c432dcaf145e5b40029b386dde0f6f33d6cbbc4f178ac81163b39dc2c1
- Size of remote file:
- 1.11 GB
- SHA256:
- 9110c060056e73010620e5a939928fe786fb5e95b981aa2c77fb3f2d1e8ecdaf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.