Instructions to use HiTZ/mbert-argmining-abstrct-en-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/mbert-argmining-abstrct-en-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HiTZ/mbert-argmining-abstrct-en-es")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HiTZ/mbert-argmining-abstrct-en-es") model = AutoModelForTokenClassification.from_pretrained("HiTZ/mbert-argmining-abstrct-en-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f367c6377f9b84d0b40087abadf1a48880a000cd3759fab13c32fb2e2d0f6767
- Size of remote file:
- 5.05 kB
- SHA256:
- ed24ac9afab1bea179b4701674fefdacd7f3cebd1c81dd62a5bc0fdf71863ccd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.