Instructions to use AIGuy1000/news-sentiment-bert-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIGuy1000/news-sentiment-bert-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AIGuy1000/news-sentiment-bert-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AIGuy1000/news-sentiment-bert-3") model = AutoModelForSequenceClassification.from_pretrained("AIGuy1000/news-sentiment-bert-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Install locally
python -m pip install git+https://huggingface.co/AIGuy1000/news-sentiment-bert-3
How to Use It:
repo_id = "AIGuy1000/news-sentiment-bert-3"
clf = pipeline("text-classification", model=repo_id)
print(clf("Financial News Headline Here."))
Output:
[{'label': 'positive', 'score': 0.9995436072349548}]
Available labels: positive, neutral, negative
- Downloads last month
- 4