Instructions to use Asif1997/Sentiment-Analysis-Finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Asif1997/Sentiment-Analysis-Finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Asif1997/Sentiment-Analysis-Finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Asif1997/Sentiment-Analysis-Finetuning") model = AutoModelForSequenceClassification.from_pretrained("Asif1997/Sentiment-Analysis-Finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Asif1997/Sentiment-Analysis-Finetuning: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/Asif1997/Sentiment-Analysis-Finetuning/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Asif1997/Sentiment-Analysis-Finetuning@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Asif1997/Sentiment-Analysis-Finetuning/resolve/refs%2Fpr%2F1/training_args.bin
3.58 kB
- Xet hash:
- 3fdfbd8b92c300ce3d7efc1248d71de8b72e653c923a5af78a46917ce0aa0ec5
- Size of remote file:
- 3.58 kB
- SHA256:
- 30cc4e4055138c4b9b2e54bbd7705b5695b70d4b92fd2ae621258c55a93c8dde
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