Instructions to use Rohan5manza/sentiment_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rohan5manza/sentiment_analysis with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Rohan5manza/sentiment_analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Rohan5manza/sentiment_analysis: direct link, hf CLI and curl.
- Browser
- Download file 295 Bytes
-
https://huggingface.co/Rohan5manza/sentiment_analysis/resolve/main/README.md
- Command line
-
hf download hf://Rohan5manza/sentiment_analysis/README.md
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curl -L -o README.md https://huggingface.co/Rohan5manza/sentiment_analysis/resolve/main/README.md
295 Bytes
metadata
license: apache-2.0
datasets:
- zeroshot/twitter-financial-news-sentiment
language:
- en
library_name: transformers
Current base models used for fine-tuning on snetiment analysis :
- Llama 3 8B ( Unsloth variety : Instruct-bnb- 4bit)" , using Unsloth and zeroshot twitter news dataset