Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use rajistics/fin_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rajistics/fin_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rajistics/fin_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rajistics/fin_sentiment") model = AutoModelForSequenceClassification.from_pretrained("rajistics/fin_sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6e917230cbc134633d1dd6c9fe270619ef068bf091799d91e133bf768f5cf21
- Size of remote file:
- 3.52 kB
- SHA256:
- dac09a0c22ef020a6be1600f8cfd87347617ffc1af7f0d5cddf82d7d8a2724c2
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