Token Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use Mhammad2023/bert-finetuned-ner-torch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mhammad2023/bert-finetuned-ner-torch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Mhammad2023/bert-finetuned-ner-torch")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Mhammad2023/bert-finetuned-ner-torch") model = AutoModelForTokenClassification.from_pretrained("Mhammad2023/bert-finetuned-ner-torch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbffb1199f2bd85c5cb6a4b87afc9ff2155ef37d6200120ff1776977a5b9c041
- Size of remote file:
- 5.3 kB
- SHA256:
- 3aeac59119cca2649c397feb8cec3bb87183420d4ac6f26ebaa6e7ce0fe5cf61
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