Instructions to use marquesafonso/bertimbau-large-ner-total with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marquesafonso/bertimbau-large-ner-total with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="marquesafonso/bertimbau-large-ner-total")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("marquesafonso/bertimbau-large-ner-total") model = AutoModelForTokenClassification.from_pretrained("marquesafonso/bertimbau-large-ner-total", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from marquesafonso/bertimbau-large-ner-total: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/marquesafonso/bertimbau-large-ner-total/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://marquesafonso/bertimbau-large-ner-total/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/marquesafonso/bertimbau-large-ner-total/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- b7e6f16e801d7b373d52c5bfdc063cfe2e0d27c194f36374173fcaad6da378f1
- Size of remote file:
- 436 MB
- SHA256:
- 84e7ada7c449c648d6f92b8efb9f03064dd55a33b146993fb126324e6797bcb8
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