Instructions to use emilys/hmBERT-CoNLL-cp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilys/hmBERT-CoNLL-cp2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="emilys/hmBERT-CoNLL-cp2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("emilys/hmBERT-CoNLL-cp2") model = AutoModelForTokenClassification.from_pretrained("emilys/hmBERT-CoNLL-cp2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from emilys/hmBERT-CoNLL-cp2: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/emilys/hmBERT-CoNLL-cp2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://emilys/hmBERT-CoNLL-cp2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/emilys/hmBERT-CoNLL-cp2/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- a6fd93ce1b8709291bb2053f62c6b180efb6953896b4ef04d82c9cedf652ae63
- Size of remote file:
- 440 MB
- SHA256:
- ac808662eb7c38c2811df59b03edefe0f58c75c7e53905279e57c18c20992f44
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