Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use varun-v-rao/roberta-base-fp-sick with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varun-v-rao/roberta-base-fp-sick with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="varun-v-rao/roberta-base-fp-sick")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("varun-v-rao/roberta-base-fp-sick") model = AutoModelForSequenceClassification.from_pretrained("varun-v-rao/roberta-base-fp-sick", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82557d3deb2e7b0afa5b23998ca0fc7409519545cf04c5ec2f82e05e0c3144e8
- Size of remote file:
- 499 MB
- SHA256:
- d9fa661484c1eb2a51e7c9e56a291846fc4d4a9a58837a48a03b8064e0689887
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