Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use davidgaofc/RM_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidgaofc/RM_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davidgaofc/RM_base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davidgaofc/RM_base") model = AutoModelForSequenceClassification.from_pretrained("davidgaofc/RM_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4ae7757eb6210db5c3d137f54b0d0bf8eb985ee323bff5ab37ff748e7c47d63
- Size of remote file:
- 2.97 MB
- SHA256:
- ad9905d0681c94157d77a652161129b069af4f1705fcca646fe471b0c5fe1510
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