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")# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29a9af26cdaec1db5e9131f57c924d9c32c615a46e13cbf5e555927126e186a0
- Size of remote file:
- 3.96 kB
- SHA256:
- 39edbd66ba185fb88b607f8d327d8be5962aaefc5de5f2838664cd1c81b43e0b
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