Instructions to use epomponio/finetuned-bert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use epomponio/finetuned-bert-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="epomponio/finetuned-bert-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("epomponio/finetuned-bert-model") model = AutoModelForSequenceClassification.from_pretrained("epomponio/finetuned-bert-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5d97d7ba8f4485d865e0d6746077cfd5bce04483cb471d2662ff31c798afe89
- Size of remote file:
- 268 MB
- SHA256:
- e0af65e01f17a15a654fafc13603c1949054c473109cf0871c17c4e5765542a0
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