Text Classification
Transformers
Safetensors
English
bert
deep-learning
huggingface
text-embeddings-inference
Instructions to use Driisa/finbert-finetuned-github with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Driisa/finbert-finetuned-github with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Driisa/finbert-finetuned-github")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Driisa/finbert-finetuned-github") model = AutoModelForSequenceClassification.from_pretrained("Driisa/finbert-finetuned-github") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8eaa1652862a3924c9b81f49c046432d3c72ad7d17e474d6a9cc90b8298d9858
- Size of remote file:
- 438 MB
- SHA256:
- 20e5552051656bb60fd4e2481047bd4c5385fd9b79a0a66ec7901dbb51469507
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