Instructions to use dhruvsangani/Sentiment-Analysis-Multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dhruvsangani/Sentiment-Analysis-Multilingual with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dhruvsangani/Sentiment-Analysis-Multilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use dhruvsangani/Sentiment-Analysis-Multilingual with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for dhruvsangani/Sentiment-Analysis-Multilingual to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for dhruvsangani/Sentiment-Analysis-Multilingual to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for dhruvsangani/Sentiment-Analysis-Multilingual to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="dhruvsangani/Sentiment-Analysis-Multilingual", max_seq_length=2048, )
- Xet hash:
- f08596a0398fe5bb5a1349a9d3c940d3b416ea529790e667513036dd2151459c
- Size of remote file:
- 45.1 MB
- SHA256:
- 54a7621293cd50510a9a7d2a92948ecc6067be44ff259f36b926d49493bb09b3
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