Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use erickdp/comprehendo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erickdp/comprehendo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="erickdp/comprehendo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("erickdp/comprehendo") model = AutoModelForSequenceClassification.from_pretrained("erickdp/comprehendo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23addead79cc133d621c7b488d0d3c89e6213461b9d48fa73679c74edac39b96
- Size of remote file:
- 4.86 kB
- SHA256:
- 7bd5dc0c48a89831ad50e403f9f49090c7ec34efa61743d5a597a3a38bb7d1a3
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