Instructions to use Agra2002/sentiment_analysis_LLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Agra2002/sentiment_analysis_LLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Agra2002/sentiment_analysis_LLM")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Agra2002/sentiment_analysis_LLM") model = AutoModelForSequenceClassification.from_pretrained("Agra2002/sentiment_analysis_LLM") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Agra2002/sentiment_analysis_LLM")
model = AutoModelForSequenceClassification.from_pretrained("Agra2002/sentiment_analysis_LLM")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
license: apache-2.0
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Agra2002/sentiment_analysis_LLM")