Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use GhylB/Sentiment_Analysis_RoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GhylB/Sentiment_Analysis_RoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GhylB/Sentiment_Analysis_RoBERTa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GhylB/Sentiment_Analysis_RoBERTa") model = AutoModelForSequenceClassification.from_pretrained("GhylB/Sentiment_Analysis_RoBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from GhylB/Sentiment_Analysis_RoBERTa: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/GhylB/Sentiment_Analysis_RoBERTa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://GhylB/Sentiment_Analysis_RoBERTa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/GhylB/Sentiment_Analysis_RoBERTa/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 13e35e82958a2397b5a081fac77d336416c406c3a07629f3a4a933697d6bbe5b
- Size of remote file:
- 499 MB
- SHA256:
- 1678e431d5fd2868edc40fa77b94a49eecb1cb15836842539764c15726ff49b1
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