Instructions to use seriouspark/find_tune_bert_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seriouspark/find_tune_bert_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="seriouspark/find_tune_bert_output")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("seriouspark/find_tune_bert_output") model = AutoModelForTokenClassification.from_pretrained("seriouspark/find_tune_bert_output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47af49b33c91dc8f90e7a6d533f9b755e3871662ea890c829b701d4b3658dace
- Size of remote file:
- 4.92 kB
- SHA256:
- 392ed041b37084cf003267db08c0901bc2f2c048fe11084beeef6f02573c060e
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