Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use itsmeandy/fin_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use itsmeandy/fin_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="itsmeandy/fin_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("itsmeandy/fin_sentiment") model = AutoModelForSequenceClassification.from_pretrained("itsmeandy/fin_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9602f711254e5550754ff7df75504201ca401079f18181c040d15dba57676e72
- Size of remote file:
- 268 MB
- SHA256:
- 9f541b181b63ca19f43df1578b78ad90273f1cdfb30f93aa4d4ae324315a8687
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.