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 pytorch_model.bin from Asif1997/Sentiment-Analysis-Finetuning: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Asif1997/Sentiment-Analysis-Finetuning/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Asif1997/Sentiment-Analysis-Finetuning/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Asif1997/Sentiment-Analysis-Finetuning/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- b4ead486ac652215e848400c043488d3ccc874bc78ef05b9940b10d699527ea5
- Size of remote file:
- 499 MB
- SHA256:
- b54002759058c886e038e1cb0478aa54388e196dd68b6352e4a6ba72ca7a17f4
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