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 training_args.bin from GhylB/Sentiment_Analysis_RoBERTa: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/GhylB/Sentiment_Analysis_RoBERTa/resolve/main/training_args.bin
- Command line
-
hf download hf://GhylB/Sentiment_Analysis_RoBERTa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/GhylB/Sentiment_Analysis_RoBERTa/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- 1ab01b41bb3a9844c7d0b9ae72d17b277137773fb5c43cd49c75ba80cbb494ab
- Size of remote file:
- 4.16 kB
- SHA256:
- 9f7bdffa6b3689bfff262b50f567022057c63b5333b5b88e408ff50ec95fbe4a
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