Text Classification
Transformers
Joblib
Safetensors
bert
sentiment-analysis
finance
macroeconomics
climate
esg
policy
ensemble
dictionary
finbert
Eval Results (legacy)
text-embeddings-inference
Instructions to use peyterho/macro-sentiment-finbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peyterho/macro-sentiment-finbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="peyterho/macro-sentiment-finbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("peyterho/macro-sentiment-finbert") model = AutoModelForSequenceClassification.from_pretrained("peyterho/macro-sentiment-finbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0b19a94d5fe4a59973aed5208489e295c234edbd92ba6e631ef8a1fc54eeb25
- Size of remote file:
- 3.2 MB
- SHA256:
- ae85888a38d8874040620d2b596073c3bc5f674ce20ac2a0bd97a493d7ee4516
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