Instructions to use DeepNeural/ner_classifier_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepNeural/ner_classifier_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DeepNeural/ner_classifier_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DeepNeural/ner_classifier_v2") model = AutoModelForTokenClassification.from_pretrained("DeepNeural/ner_classifier_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from DeepNeural/ner_classifier_v2: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/DeepNeural/ner_classifier_v2/resolve/main/model.safetensors
- Command line
-
hf download hf://DeepNeural/ner_classifier_v2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/DeepNeural/ner_classifier_v2/resolve/main/model.safetensors
436 MB
- Xet hash:
- 34d8e09e587b8ea6e8e82fdd6948d95e892cebcf97baaa8876b17109f5707d30
- Size of remote file:
- 436 MB
- SHA256:
- 36c908ec04565c99448d3acd408e477a47175aeb130c847742f859b9c21047cd
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