Instructions to use fbaigt/proc_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fbaigt/proc_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fbaigt/proc_roberta")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fbaigt/proc_roberta") model = AutoModel.from_pretrained("fbaigt/proc_roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0c8986e3254662988b0b48ad24877065abc27c915664ed8877f0a42a0b6080c
- Size of remote file:
- 499 MB
- SHA256:
- 96d4f667d32c80763ecd9d3a6eeed0d0b568a21e663225233aced14cbb69db75
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