Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Junr-syl/sentiments_analysis_Roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Junr-syl/sentiments_analysis_Roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Junr-syl/sentiments_analysis_Roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Junr-syl/sentiments_analysis_Roberta") model = AutoModelForSequenceClassification.from_pretrained("Junr-syl/sentiments_analysis_Roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Junr-syl/sentiments_analysis_Roberta: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Junr-syl/sentiments_analysis_Roberta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Junr-syl/sentiments_analysis_Roberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Junr-syl/sentiments_analysis_Roberta/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 652e7ec052da5c4da4b8463fded961caef9b573a5f06608b0047d6312cc7be71
- Size of remote file:
- 499 MB
- SHA256:
- 2a7c8dbf6ec5480c399219006f6fbc995124b11f35fb68784a6899e24788d5a6
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