Text Classification
Transformers
TensorBoard
Safetensors
English
bert
finbert
finance
sentiment-analysis
tech-stocks
text-embeddings-inference
Instructions to use assix-research/FinBERT-Tech-Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use assix-research/FinBERT-Tech-Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="assix-research/FinBERT-Tech-Sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("assix-research/FinBERT-Tech-Sentiment") model = AutoModelForSequenceClassification.from_pretrained("assix-research/FinBERT-Tech-Sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3e26fc74ed6af8f15373555db52b5441265cc07ba9b71f0113f5d3afe564d75
- Size of remote file:
- 5.91 kB
- SHA256:
- 72e84956f625138d3e8cd9173e6e5f104568e5f6e1d4d06fb0c7ffa414a6861e
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