Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ThomasLI/roberta-base-finetuned-classification-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThomasLI/roberta-base-finetuned-classification-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThomasLI/roberta-base-finetuned-classification-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThomasLI/roberta-base-finetuned-classification-v2") model = AutoModelForSequenceClassification.from_pretrained("ThomasLI/roberta-base-finetuned-classification-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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oid sha256:6259c561b0ad0f0c0a54d61e4a42812051908138174ee9de682e3abbe8614d82
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size 498617024
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