Text Classification
Transformers
Safetensors
PyTorch
bert
sentiment-analysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use ashwini10521/finetuned_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashwini10521/finetuned_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ashwini10521/finetuned_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ashwini10521/finetuned_bert") model = AutoModelForSequenceClassification.from_pretrained("ashwini10521/finetuned_bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7afb8ff3281e31dee062dba4282a6fc13a538f19f38fb74e8a350a84ec447eaa
- Size of remote file:
- 5.2 kB
- SHA256:
- 2b72cdbc41616ce99a92adb244d06383fa1c2a91b15210bc6d6db567a7bf942e
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