Instructions to use mircoboettcher/bert-ecom-ner-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mircoboettcher/bert-ecom-ner-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mircoboettcher/bert-ecom-ner-test")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mircoboettcher/bert-ecom-ner-test") model = AutoModelForTokenClassification.from_pretrained("mircoboettcher/bert-ecom-ner-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dfce62049cd8dde5f1e2e92081053c88b6b69d39e430a017e24c9d663a830701
- Size of remote file:
- 436 MB
- SHA256:
- e9d13a090fe36021d65608e7080664c69c8bfbfc32821b0b3b9895bb83f67e28
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