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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("erickdp/comprehendo") model = AutoModelForSequenceClassification.from_pretrained("erickdp/comprehendo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from erickdp/comprehendo: direct link, hf CLI and curl.
- Browser
- Download file 738 MB
-
https://huggingface.co/erickdp/comprehendo/resolve/main/model.safetensors
- Command line
-
hf download hf://erickdp/comprehendo/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/erickdp/comprehendo/resolve/main/model.safetensors
738 MB
- Xet hash:
- a2017f8b1c0e6889406b1a59d85da2488f8e8e8b4a2bc790d0abe151d274cac1
- Size of remote file:
- 738 MB
- SHA256:
- a243689b46fde2b0420b4b502df2ed21d40d053221f1f53b2b59c73bc1a52c6f
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