Text Classification
Transformers
Safetensors
English
bert
financial-sentiment
sentiment-analysis
finance
nlp
Eval Results (legacy)
text-embeddings-inference
Instructions to use codealchemist01/financial-sentiment-improved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codealchemist01/financial-sentiment-improved with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="codealchemist01/financial-sentiment-improved")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("codealchemist01/financial-sentiment-improved") model = AutoModelForSequenceClassification.from_pretrained("codealchemist01/financial-sentiment-improved") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0bdcdc93b55ce3de1e4a8ea16b3bc722b8555dc2b5ad032ef834e58ac9897904
- Size of remote file:
- 5.84 kB
- SHA256:
- 3cb2ecd9bb017dca59b8123a0bc341b04a5a2fec62dea1faccf98aad898c9162
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