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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d5060c2ea7a11252e57892e0ae0482d003e4b0f8487ae1b69bc212bb63e02d2
- Size of remote file:
- 438 MB
- SHA256:
- 3ced80768c631b64def495b70ac51d8211c6136626c4846a5ccca1d3423f96fb
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