Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Sharpaxis/FIN_BERT_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharpaxis/FIN_BERT_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sharpaxis/FIN_BERT_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sharpaxis/FIN_BERT_sentiment") model = AutoModelForSequenceClassification.from_pretrained("Sharpaxis/FIN_BERT_sentiment") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- Tokenizers 0.20.3
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### code to use in pipeline
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import matplotlib.pyplot as plt
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import plotly.graph_objects as go
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%matplotlib inline
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- Tokenizers 0.20.3
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### code to use in pipeline
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'''python
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import matplotlib.pyplot as plt
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import plotly.graph_objects as go
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%matplotlib inline
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