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:
- 9b583d66ef4103c213306b3fb05a8eec76c23c54b31910e6e39af8e1bcf62ab7
- Size of remote file:
- 4.54 kB
- SHA256:
- b3f392725592b40b6a97e3b1ab5dee5e4b8b2f9281df31d5c2603a2810e681ed
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