Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use suhasy2/fin_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suhasy2/fin_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="suhasy2/fin_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("suhasy2/fin_sentiment") model = AutoModelForSequenceClassification.from_pretrained("suhasy2/fin_sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98b994371e882d9a58c775374f7c73834ede3d9fa89dc9b1ff4f98c9e87abb9d
- Size of remote file:
- 3.44 kB
- SHA256:
- b91ecc6796144ac71a8d5dc9b51d5fd6932dfd7eac51520cc053f132c175da4b
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