Instructions to use devansvd/bert-model-test-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devansvd/bert-model-test-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="devansvd/bert-model-test-2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("devansvd/bert-model-test-2") model = AutoModelForTokenClassification.from_pretrained("devansvd/bert-model-test-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e2eb642629de33d71b685b278b90f8a696fc3238d140791bacac2217c126806
- Size of remote file:
- 436 MB
- SHA256:
- 69ed5a455e6bf77143c9790219ee6bbe1f4508b5b848d250d9432dc8f546a5d7
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